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Author SHA1 Message Date
Josh Hawkins f4d25ccbcc docs 2026-08-22 11:55:16 -05:00
Josh Hawkins 6d0733d18c read the exec override from an import time snapshot
environment_vars is exported into os.environ, and is_go2rtc_arbitrary_exec_allowed read os.environ live, so the config file could enable exec sources. Snapshot the variable at import, which runs before any config is loaded.
2026-08-22 11:55:16 -05:00
Josh Hawkins 027bafdb29 use the shared substitution namespace in go2rtc config
The generator rebuilt the namespace itself from os.environ and a hardcoded /run/secrets, so it never saw environment_vars or CREDENTIALS_DIRECTORY, and str.format made any stray brace fatal. It now installs the FRIGATE_ names from environment_vars and substitutes streams the same way every other field does.
2026-08-22 11:55:16 -05:00
Josh Hawkins 1355075fda add secrets.yaml and merge substitution sources by precedence
FRIGATE_ENV_VARS was built once at import from container env and /run/secrets, and the environment_vars validator overwrote it unconditionally, so the block beat the deployment and nothing could be re-read. Sources are now separate dicts merged lowest to highest (environment_vars, secrets.yaml, container env, credentials directory), re-read at the top of every parse, and a collision warns once naming the winner. An undefined {FRIGATE_*} raises a ValueError subclass so pydantic reports the field instead of a KeyError traceback.
2026-08-22 11:55:16 -05:00
Josh Hawkins 01bb9f3f37 fix clip download deadlock from unread ffmpeg stderr (#24032)
ffmpeg's stderr was piped but never read, so recording segments that generate more than 64 KB of ffmpeg warnings blocked ffmpeg mid-write, stranding the streaming thread and its anyio threadpool token for good. Enough of those and every sync endpoint stops responding until restart. The trigger is how noisy the segments are, not how long the clip is.

Send stderr to a temp file instead, and guarantee ffmpeg teardown and playlist cleanup on every exit path, including client disconnect.

Also fixes two bugs the deadlock hid: the failure branch was unreachable because returncode is None mid-loop, so the playlist file leaked and ffmpeg's logs were never reported. Playlist files now get a unique name so concurrent requests for one range cannot delete each other's input.

Extracts the terminate helper motion search already had into frigate/util/ffmpeg.py, now shared by both streaming call sites.
2026-08-22 11:40:42 -05:00
Josh Hawkins b91fb05314 fix the model lookup KeyError for cameras added at runtime (#24026) 2026-08-22 11:40:42 -05:00
Josh Hawkins 199bea081c Add import/export for camera group layouts and per-camera streaming settings (#24025)
* add import/export for camera group layouts and streaming settings

Camera group layouts and per-camera streaming settings are stored in the browser's IndexedDB, so they are tied to a single browser on a single device. Users with more than one device have to rebuild every group layout and re-pick every camera's stream settings by hand, and clearing browser data loses the work.

Add a Backup & Restore card to Settings > UI Settings that exports these settings to a JSON file and imports that file on another device. Import shows a confirmation dialog with per-section counts, switches for layouts, streaming settings, and UI preferences, and warnings about camera groups or cameras in the file that are not on this server.

Server-side storage is deliberately avoided. These are per-device presentation settings: a layout arranged for a desktop is wrong on a tablet, and continuous full-resolution streams that are free on a wired LAN are not on a phone. An explicit file moves settings only when the user chooses to move them.

Implementation notes:

- web/src/utils/uiSettingsTransfer.ts owns a registry of transferable IndexedDB keys. Each entry records whether the key is user-namespaced, matching which persistence hook wrote it, plus a zod schema for its value.
- Only registry-known keys are ever written, and only when their value passes that schema. The file format deliberately lets unknown keys survive parsing, so this filter is what prevents a hand-edited file from writing arbitrary storage keys or out-of-range values.
- Export falls back to the legacy un-namespaced key, because the username migration runs lazily on first mount of each owning hook.
- Streaming settings merge per group rather than replacing the whole map, so groups configured only on the receiving device survive.
- Import writes storage and then reloads, because useUserPersistence reads a key only on mount and StreamingSettingsProvider would otherwise write its stale in-memory state back over the import.
- playbackBandwidthEstimate, frigate-search-history, and live-layout are excluded: the first two are measurements and user data rather than preferences, and live-layout's default is derived from the device.

* merge imported streaming settings per camera instead of per group
2026-08-22 11:40:42 -05:00
Nicolas MowenandJosh Hawkins 07ba2357e6 Implement UI for managing multiple models (#24023)
* Implement hardware detection and UI management

* Cleanup Frigate+ detection

* Don't count model as changed

* Fixes for audio map error

* Add descriptions

* Enforce that all model must exist

* Fix hardware picking

* Docs fixes

* WebUI cleanup

* Cleanup handling of scenes

* UI refinement

* Cleanup recommended UI

* test fixews
2026-08-22 11:40:42 -05:00
Josh Hawkins 79ea68caa2 Base emergency cleanup on the streams a camera is currently recording (#24022)
* gate emergency cleanup bandwidth on the streams a camera currently records

* settle bandwidth samples per stream instead of per camera

* fix mypy
2026-08-22 11:40:42 -05:00
Nicolas MowenandJosh Hawkins 5c9c02002f Refactor detector and model management (#23995)
* Refactor detector and model management

* Fix model resolution field
2026-08-22 11:40:42 -05:00
Ersa Oktavian RamadanandJosh Hawkins 7b42d94bfe Add audio labelmap grouping (#24004)
Allow audio classes to be grouped under a shared configured label.

Keep audio overrides separate from object labels and retain only the highest-scoring grouped detection.

Refs #23967
2026-08-22 11:40:42 -05:00
Josh Hawkins 0f5ed8822d Show main and sub stream usage separately in Storage Metrics (#24015)
* backend

* frontend

* docs

* test

* report null instead of 0 for a stream with no cached bandwidth sample
2026-08-22 11:40:42 -05:00
Josh Hawkins af537b9479 Refactor MQTT (#24010)
* refactor mqtt so that Frigate owns the transport lifecycle instead of delegating it to paho

* release the shutdown barrier on worker crash and replay retained publishes the broker never acked

* collapse in-flight retained values by topic and release the shutdown barrier from a finally

* replay the outage buffer before the publish queue so newer values are not reverted
2026-08-22 11:40:42 -05:00
Josh Hawkins 2395a82639 Refactor birdseye activity modes as a list and add alerts/detections (#24012)
* backend

* tests

* frontend and i18n

* e2e test schema

* docs
2026-08-22 11:40:42 -05:00
Josh Hawkins e8c7f4b2ff Improve History's seek startup time and recordings query performance (#24011)
* serve a segment startup ladder so seeks begin playing sooner

nginx-vod was handed one 10s segment per recording file, so every playlist start had to download and decode a full segment before the first frame. Declare real keyframe data per clip and let nginx cut short leading segments from it.

- add vod_bootstrap_segment_durations 1000/2000/4000 so each playlist starts with 1s/2s/4s segments before settling at 10s
- emit real clip-relative keyFrameDurations (plus firstKeyFrameOffset when nonzero) from the recording keyframe index; rows without an index keep the whole-clip declaration, the only safe cut without keyframe knowledge
- drop the manifest's segment_duration field, which was always inert: nginx-vod parses only camelCase segmentDuration
- rebuild the player source at the seek target, quantized to a 10s grid, so the ladder applies to every seek and seek URLs stay repeatable for nginx's mapping and response caches
- route the seek model, in-range checks, and the stale-report guard through the source window rather than the chunk range
- bridge repositioning seeks (>2s from the last played timestamp) through the preview player and hold the release anchor one commit, so neither path paints a stale frame
- clear a pending loading timer before replacing it; an orphaned timer escaped onPlaying's clearTimeout and flashed loading mid-playback

* keep recordings queries on their indexes

Several recordings queries degraded into full scans or large sorts on big databases: the planner ignored index order, or the query shape gave it nothing tight to seek on. Reshape them into bounded seeks and add the composite index the per-stream lookups need.

- index recordings on (camera, stream_type, start_time DESC) and drop the (camera, stream_type) index it supersedes
- walk the recordings summary day by day with EXISTS probes and per-camera MIN/MAX seeks, skipping ahead over empty gaps instead of bucketing every row for the requested cameras
- run the summary endpoint on the event loop rather than the threadpool
- bound the unavailable-recordings query by start_time per camera and merge the results in Python
- bound the expire query's start_time so it seeks the retention window instead of scanning a camera's whole history
- enumerate deleted cameras with one index seek each rather than a camera NOT IN (...) scan
- compute bandwidth with segment_size filtered in a CASE projection; as a WHERE predicate it baited the planner into the (camera, segment_size) index plus a full sort of the camera's history
- fall back to a 1000-segment window when the recent 100 are all zero-size, so an ingest glitch doesn't report zero bandwidth
- limit the needs_refresh count instead of counting every segment
- cover sub-only and sparse calendar days, midnight-spanning day attribution, multi-camera gap merging, deleted-camera expiry, and zero-size segment runs

* fix mypy
2026-08-22 11:40:42 -05:00
Josh Hawkins f7afec3aa7 Enable PTZ control setup in the Add Camera Wizard (#23444)
* add ptz controls to camera via wizard when onvif has already been probed

* i18n

* add e2e test

* backend add and remove subscriber

* tweaks

* turn on switch by default if pan and/or tilt capability is available

* fix test
2026-08-22 11:40:42 -05:00
Josh Hawkins d67304a84d Add sub stream recording with adaptive quality playback (#24009)
* add sub stream recording with adaptive quality playback

Optionally record a second, lower bitrate stream alongside the main
recording stream via a `record_sub` input role and `record.sub` config block, with its own retention windows.
Recordings rows now carry the stream type plus the media details needed to serve both streams from one manifest: video codec, audio presence, audio codec and rate, and a record-time keyframe index.

Playback resolves coverage across both streams and merges them into a single VOD sequence, falling back to a discontinuity manifest with per-clip init segments when the media signatures differ. The player exposes a quality selector, and an auto governor picks the stream from stall time, bandwidth, codec support, and the save-data hint.

* fix tests and i18n
2026-08-22 11:40:42 -05:00
Josh Hawkins 8de6216c61 stop creating a config subscriber per capture thread (#24002) 2026-08-22 11:40:42 -05:00
Josh Hawkins 80e0bbeda6 Guard lookups when adding/deleting cameras at runtime (#23994)
* Guard object processor queue handlers against unknown cameras

* Skip embeddings post processing for removed cameras

* End review segments for removed cameras

* Drop queued autotracker moves for removed cameras

* Release tracked event thumbnails when skipping a removed camera

* Add locked accessors for camera states

* Read camera states through the processor accessors

* Guard output and recording paths against cameras not yet known

* Resolve camera state once in ONVIF, notification, and transcription paths
2026-08-22 11:40:42 -05:00
Ersa Oktavian RamadanandJosh Hawkins 4147d01374 Refactor Birdseye activity types as composable booleans (#23940)
* Add combined motion and object Birdseye mode

Add a motion_objects mode that keeps Birdseye active when motion is detected or a confirmed tracked object is present, including stationary objects.

Wire the mode through configuration, runtime commands, API schemas, documentation, and UI labels. Exclude false-positive trackers and add regression coverage for Birdseye activation and MQTT validation.

* Refactor Birdseye activity types as booleans

Replace combination-specific Birdseye modes with composable boolean activity types for motion, active objects, stationary objects, and continuous display.

Preserve legacy single-mode configuration and MQTT inputs, support canonical comma-separated MQTT combinations, and allow scalar YAML values to be replaced by nested settings through the config API.

* Preserve OpenVINO config translations

Regenerate the configuration translations with the OpenVINO detector schema available so the unrelated production detector labels remain intact.

* Preserve partial Birdseye mode overrides

Allow an empty activity selection with a canonical NONE MQTT state so partial camera and profile overrides can disable inherited flags without failing validation.

Add regression coverage for camera and profile inheritance, document the NONE contract, and keep the generated schema fixture scoped to Birdseye.

* Address Birdseye activity review feedback

Move scalar mode compatibility into the 0.18-1 config migration and reject empty activity selections instead of publishing a NONE state.

Pass activity signals through a frozen dataclass, preserve existing active-object tracker behavior, and require confirmed stationary objects. Revert the generic YAML mutation and cover migration, inheritance, MQTT, and activation regressions.

* Move Birdseye migration to 0.19

Use the 0.19-0 configuration revision for converting scalar Birdseye modes to composable activity flags, and update the migration regression coverage accordingly.

* Remove Birdseye migration test

Drop the dedicated config migration test as requested during review while retaining the 0.19-0 migration implementation.
2026-08-22 11:40:42 -05:00
Josh Hawkins a9d09f8a81 Fix birdseye layout overlap with mixed landscape/portrait cameras (#22917)
* fix birdseye layout calculation

replace the two pass layout with a single pass pixel space algorithm

* add test
2026-08-22 11:40:42 -05:00
Nicolas MowenandJosh Hawkins fe14d4ef09 Don't require object type for parameter in categorized names tool 2026-08-22 11:40:42 -05:00
079bd802f2 Dynamically resolve Intel NPU (#23761)
* Add support for newer Intel NPU busy time counter

* Resolve Intel NPU device dynamically

---------

Co-authored-by: Filious Louis <1417132+fjlouis@users.noreply.github.com>
2026-08-22 11:40:42 -05:00
DoFabienandJosh Hawkins 163d3b865e Improve recording timeline and VOD query performance (#23862)
* Improve recording timeline and VOD query performance

* Add recording query boundary tests
2026-08-22 11:40:42 -05:00
Nicolas MowenandJosh Hawkins ca6d327f74 GenAI Chat Prompt Refinements (#23864)
* Prompt refactoring and optimization

* Update spec
2026-08-22 11:40:42 -05:00
Nicolas MowenandJosh Hawkins 8700227704 Update to 0.19 2026-08-22 11:40:41 -05:00
Nicolas MowenandGitHub ad79e666eb API Consistency / Security Fixes (#24057)
CI / AMD64 Build (push) Canceled after 0s
CI / ARM Build (push) Canceled after 0s
CI / Jetson Jetpack 6 (push) Canceled after 0s
CI / ARM Extra Build (push) Canceled after 0s
CI / Synaptics Build (push) Canceled after 0s
CI / AMD64 Extra Build (push) Canceled after 0s
CI / Assemble and push default build (push) Canceled after 0s
* Make review user read status consistent with other APIs

* Validate URLs for web push endpoint

* Validate the role for a custom viewer, rate limit password changing

* Cleanup
2026-08-22 11:08:24 -05:00
Nicolas MowenandGitHub fc79aeab5e Fix review summary report analysis creation to be scoped for users with full camera access only (#24056)
* Fix review summary analysis

* Add ability to scope based on full camera access
2026-08-22 11:06:01 -05:00
223 changed files with 19704 additions and 5289 deletions
+1 -1
View File
@@ -1,7 +1,7 @@
default_target: local
COMMIT_HASH := $(shell git log -1 --pretty=format:"%h"|tail -1)
VERSION = 0.18.0
VERSION = 0.19.0
IMAGE_REPO ?= ghcr.io/blakeblackshear/frigate
GITHUB_REF_NAME ?= $(shell git rev-parse --abbrev-ref HEAD)
BOARDS= #Initialized empty
@@ -3,13 +3,12 @@
import json
import os
import sys
from pathlib import Path
from typing import Any
from ruamel.yaml import YAML
sys.path.insert(0, "/opt/frigate")
from frigate.config.env import substitute_frigate_vars
from frigate.config.env import apply_config_env_vars, substitute_frigate_vars
from frigate.const import (
BIRDSEYE_PIPE,
LIBAVFORMAT_VERSION_MAJOR,
@@ -25,15 +24,6 @@ sys.path.remove("/opt/frigate")
yaml = YAML()
FRIGATE_ENV_VARS = {k: v for k, v in os.environ.items() if k.startswith("FRIGATE_")}
# read docker secret files as env vars too
if os.path.isdir("/run/secrets"):
for secret_file in os.listdir("/run/secrets"):
if secret_file.startswith("FRIGATE_"):
FRIGATE_ENV_VARS[secret_file] = (
Path(os.path.join("/run/secrets", secret_file)).read_text().strip()
)
config_file = find_config_file()
try:
@@ -47,6 +37,20 @@ try:
except FileNotFoundError:
config: dict[str, Any] = {}
# No validator runs here, so install environment_vars ourselves. FRIGATE_
# names only: anything else lands in os.environ, where the exec gate reads
# GO2RTC_ALLOW_ARBITRARY_EXEC.
config_env_vars = config.get("environment_vars")
apply_config_env_vars(
{
key: value
for key, value in config_env_vars.items()
if str(key).startswith("FRIGATE_")
}
if isinstance(config_env_vars, dict)
else {}
)
go2rtc_config: dict[str, Any] = config.get("go2rtc", {})
# Need to enable CORS for go2rtc so the frigate integration / card work automatically
@@ -113,7 +117,7 @@ for name in list(go2rtc_config.get("streams", {})):
if isinstance(stream, str):
try:
formatted_stream = stream.format(**FRIGATE_ENV_VARS)
formatted_stream = substitute_frigate_vars(stream)
if is_restricted_go2rtc_source(formatted_stream):
print(
f"[ERROR] Stream '{name}' uses a restricted source (echo/expr/exec) which is disabled by default for security. "
@@ -122,7 +126,7 @@ for name in list(go2rtc_config.get("streams", {})):
del go2rtc_config["streams"][name]
continue
go2rtc_config["streams"][name] = formatted_stream
except KeyError as e:
except ValueError as e:
print(
"[ERROR] Invalid substitution found, see https://docs.frigate.video/configuration/restream#advanced-restream-configurations for more info."
)
@@ -132,7 +136,7 @@ for name in list(go2rtc_config.get("streams", {})):
filtered_streams = []
for i, stream_item in enumerate(stream):
try:
formatted_stream = stream_item.format(**FRIGATE_ENV_VARS)
formatted_stream = substitute_frigate_vars(stream_item)
if is_restricted_go2rtc_source(formatted_stream):
print(
f"[ERROR] Stream '{name}' item {i + 1} uses a restricted source (echo/expr/exec) which is disabled by default for security. "
@@ -141,7 +145,7 @@ for name in list(go2rtc_config.get("streams", {})):
continue
filtered_streams.append(formatted_stream)
except KeyError as e:
except ValueError as e:
print(
"[ERROR] Invalid substitution found, see https://docs.frigate.video/configuration/restream#advanced-restream-configurations for more info."
)
@@ -75,6 +75,12 @@ http {
vod_align_segments_to_key_frames on;
vod_manifest_segment_durations_mode accurate;
vod_ignore_edit_list on;
# short leading segments at each playlist start; sources start at
# the seek target, so the ladder applies to every seek. Only
# effective when clips declare real keyFrameDurations
vod_bootstrap_segment_durations 1000;
vod_bootstrap_segment_durations 2000;
vod_bootstrap_segment_durations 4000;
vod_segment_duration 10000;
# MPEG-TS settings (not used when fMP4 is enabled, kept for reference)
File diff suppressed because it is too large Load Diff
+102 -53
View File
@@ -56,17 +56,6 @@ mqtt:
# 2 = exactly once
qos: 0
# Optional: Detectors configuration. Defaults to a single CPU detector
detectors:
# Required: name of the detector
detector_name:
# Required: type of the detector
# Frigate provides many types, see https://docs.frigate.video/configuration/object_detectors for more details (default: shown below)
# Additional detector types can also be plugged in.
# Detectors may require additional configuration.
# Refer to the Detectors configuration page for more information.
type: cpu
# Optional: Database configuration
database:
# The path to store the SQLite DB (default: shown below)
@@ -157,44 +146,56 @@ auth:
- front_door
- back_yard
# Optional: model modifications
# Optional: object detection models. Defaults to a single model on a CPU detector.
# NOTE: The default values are for the EdgeTPU detector.
# Other detectors will require the model config to be set.
model:
# Required: path to the model. Frigate+ models use plus://<model_id> (default: automatic based on detector)
path: /edgetpu_model.tflite
# Required: path to the labelmap (default: shown below)
labelmap_path: /labelmap.txt
# Required: Object detection model input width (default: shown below)
width: 320
# Required: Object detection model input height (default: shown below)
height: 320
# Required: Object detection model input colorspace
# Valid values are rgb, bgr, or yuv. (default: shown below)
input_pixel_format: rgb
# Required: Object detection model input tensor format
# Valid values are nhwc, nchw, hwnc, or hwcn (default: shown below)
input_tensor: nhwc
# Optional: Data type of the model input tensor
# Valid values are float, float_denorm, or int (default: shown below)
input_dtype: int
# Required: Object detection model architecture, used by detectors that support more
# than one model type (openvino, onnx, rknn, memryx, axengine, synaptics, and others)
# Valid values are ssd, yolox, yolonas, yolo-generic, rfdetr, dfine (default: shown below)
model_type: ssd
# Required: Label name modifications. These are merged into the standard labelmap.
labelmap:
2: vehicle
# Optional: Map of object labels to their attribute labels (default: depends on model)
attributes_map:
person:
- amazon
- face
car:
- amazon
- fedex
- license_plate
- ups
models:
# Optional: the camera environment this model is for (default: shown below)
# Cameras select a model by setting detect -> scene to a matching value, and
# a model with a scene of all is used by any camera that does not set one.
# Valid values are all, indoor, outdoor, indoor_thermal, outdoor_thermal
- scene: all
# Required: hardware this model runs on, as <detector> or <detector>:<device>
# See https://docs.frigate.video/configuration/object_detectors for the
# detectors available and the devices each one accepts. All of a model's
# devices must use the same detector. Listing the same device more than once
# runs additional inference processes on it.
devices:
- edgetpu:pci:0
# Required: path to the model. Frigate+ models use plus://<model_id> (default: automatic based on detector)
path: /edgetpu_model.tflite
# Required: path to the labelmap (default: shown below)
labelmap_path: /labelmap.txt
# Required: Object detection model input width (default: shown below)
width: 320
# Required: Object detection model input height (default: shown below)
height: 320
# Required: Object detection model input colorspace
# Valid values are rgb, bgr, or yuv. (default: shown below)
input_pixel_format: rgb
# Required: Object detection model input tensor format
# Valid values are nhwc, nchw, hwnc, or hwcn (default: shown below)
input_tensor: nhwc
# Optional: Data type of the model input tensor
# Valid values are float, float_denorm, or int (default: shown below)
input_dtype: int
# Required: Object detection model architecture, used by detectors that support more
# than one model type (openvino, onnx, rknn, memryx, axengine, synaptics, and others)
# Valid values are ssd, yolox, yolonas, yolo-generic, rfdetr, dfine (default: shown below)
model_type: ssd
# Required: Label name modifications. These are merged into the standard labelmap.
labelmap:
2: vehicle
# Optional: Map of object labels to their attribute labels (default: depends on model)
attributes_map:
person:
- amazon
- face
car:
- amazon
- fedex
- license_plate
- ups
# Optional: Audio Events Configuration
# NOTE: Can be overridden at the camera level
@@ -217,6 +218,8 @@ audio:
- fire_alarm
- speech
- yell
# Optional: Audio label name modifications. These are merged into the standard audio labelmap.
labelmap: {}
# Optional: Filters to configure detection.
filters:
# Label that matches label in listen config.
@@ -251,11 +254,15 @@ birdseye:
# Optional: Encoding quality of the mpeg1 feed (default: shown below)
# 1 is the highest quality, and 31 is the lowest. Lower quality feeds utilize less CPU resources.
quality: 8
# Optional: Mode of the view. Available options are: objects, motion, and continuous
# objects - cameras are included if they have had a tracked object within the last 30 seconds
# motion - cameras are included if motion was detected in the last 30 seconds
# continuous - all cameras are included always
mode: objects
# Optional: Activity types that include cameras in Birdseye (default: shown below)
# Multiple activity types can be listed at the same time.
# continuous: all cameras are included always
# motion: included if motion was detected within the inactivity threshold
# all_objects: included if a tracked object was present within the inactivity threshold
# alerts: included while an alert review item is in progress
# detections: included while a detection review item is in progress
modes:
- all_objects
# Optional: Threshold for camera activity to stop showing camera (default: shown below)
inactivity_threshold: 30
# Optional: Configure the birdseye layout
@@ -287,6 +294,8 @@ ffmpeg:
detect: -threads 2 -f rawvideo -pix_fmt yuv420p
# Optional: output args for record streams (default: shown below)
record: preset-record-generic
# Optional: output args for sub stream record streams (default: the record output args above)
# record_sub: preset-record-generic
# Optional: Time in seconds to wait before ffmpeg retries connecting to the camera. (default: shown below)
# If set too low, frigate will retry a connection to the camera's stream too frequently, using up the limited streams some cameras can allow at once
# If set too high, then if a ffmpeg crash or camera stream timeout occurs, you could potentially lose up to a maximum of retry_interval second(s) of footage
@@ -306,6 +315,10 @@ detect:
width: 1280
# Optional: height of the frame for the input with the detect role (default: use native stream resolution)
height: 720
# Optional: the environment this camera looks at, which picks the model it runs on
# (default: the model with a scene of all)
# Valid values are all, indoor, outdoor, indoor_thermal, outdoor_thermal
scene: outdoor
# Optional: desired fps for your camera for the input with the detect role (default: shown below)
# NOTE: Recommended value of 5. Ideally, try and reduce your FPS on the camera.
fps: 5
@@ -637,6 +650,42 @@ record:
# For example, if the camera retain mode is "motion", the segments without motion are
# never stored, so setting the mode to "all" here won't bring them back.
mode: motion
# Optional: Sub stream recording settings
# Records a second, lower quality stream for quality selection during playback
# and extended low quality retention. Requires the record_sub role to be assigned
# to one of the camera's inputs.
sub:
# Optional: Enable sub stream recording (default: shown below)
# NOTE: Recording must also be enabled for sub stream recording to run.
enabled: False
# Optional: Continuous retention settings for sub stream recordings
continuous:
# Optional: Number of days to retain sub stream recordings regardless of tracked objects or motion (default: shown below)
days: 0
# Optional: Motion retention settings for sub stream recordings
motion:
# Optional: Number of days to retain sub stream recordings triggered by motion (default: shown below)
days: 0
# Optional: Retention settings for sub stream recordings of alerts
# NOTE: Pre and post capture windows are taken from the main alerts config above.
alerts:
# Required: Retention days (default: shown below)
days: 10
# Optional: Mode for retention. (default: shown below)
# all - save all sub stream recording segments for alerts regardless of activity
# motion - save all sub stream recording segments for alerts with any detected motion
# active_objects - save all sub stream recording segments for alerts with active/moving objects
mode: motion
# Optional: Retention settings for sub stream recordings of detections
# NOTE: Pre and post capture windows are taken from the main detections config above.
detections:
# Required: Retention days (default: shown below)
days: 10
# Optional: Mode for retention. (default: shown below)
# all - save all sub stream recording segments for detections regardless of activity
# motion - save all sub stream recording segments for detections with any detected motion
# active_objects - save all sub stream recording segments for detections with active/moving objects
mode: motion
# Optional: Configuration for the snapshots written to the clips directory for each tracked object
# Timestamp, bounding_box, crop and height settings are applied by default to API requests for snapshots.
@@ -888,7 +937,7 @@ cameras:
# Required: the path to the stream
# NOTE: path may include environment variables or docker secrets, which must begin with 'FRIGATE_' and be referenced in {}
- path: rtsp://viewer:{FRIGATE_RTSP_PASSWORD}@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2
# Required: list of roles for this stream. valid values are: audio,detect,record
# Required: list of roles for this stream. valid values are: audio,detect,record,record_sub
# NOTICE: In addition to assigning the audio, detect, and record roles
# they must also be enabled in the camera config.
roles:
+46 -33
View File
@@ -63,15 +63,9 @@ go2rtc:
### `environment_vars`
This section can be used to set environment variables for those unable to modify the environment of the container, like within Home Assistant OS. Docker users should set environment variables in their `docker run` command (`-e FRIGATE_MQTT_PASSWORD=secret`) or `docker-compose.yml` file (`environment:` section) instead. Note that values set here are stored in plain text in your config file, so if the goal is to keep credentials out of your configuration, use Docker environment variables or Docker secrets instead.
This section sets environment variables in the Frigate process for those unable to modify the environment of the container, like within Home Assistant OS. It's meant for process settings such as `LIBVA_DRIVER_NAME` or the TensorFlow thread counts below. Docker users should set environment variables in their `docker run` command (`-e LIBVA_DRIVER_NAME=i965`) or `docker-compose.yml` file (`environment:` section) instead. Values set here are stored in plain text in your config file, so credentials belong in `secrets.yaml`, Docker environment variables, or Docker secrets instead.
Variables prefixed with `FRIGATE_` can be referenced in config fields that support environment variable substitution (such as MQTT host and credentials, camera stream URLs, and ONVIF host and credentials) using the `{FRIGATE_VARIABLE_NAME}` syntax.
:::note
The `go2rtc` section is an exception. go2rtc runs as a separate process, so its stream definitions can only be substituted with variables that exist in the container's environment (set via Docker `-e`, the `environment:` section of `docker-compose.yml`, or Docker secrets). Variables defined in the `environment_vars` block above are not available to go2rtc streams. Home Assistant app users, who cannot set container environment variables, must instead put credentials directly in their go2rtc stream URLs.
:::
Names prefixed with `FRIGATE_` set here also take part in `{FRIGATE_VARIABLE_NAME}` substitution (see [below](#substitution-sources-and-precedence)), but `secrets.yaml` is the better home for them.
<ConfigTabs>
<TabItem value="ui">
@@ -80,23 +74,17 @@ Navigate to <NavPath path="Settings > System > Environment variables" /> to add
| Field | Description |
| ----------------- | --------------------------------------------------------- |
| **Variable name** | The environment variable name (e.g., `FRIGATE_MQTT_USER`) |
| **Variable name** | The environment variable name (e.g., `LIBVA_DRIVER_NAME`) |
| **Value** | The value for the variable |
Variables defined here can be referenced elsewhere in your configuration using the `{FRIGATE_VARIABLE_NAME}` syntax.
Names prefixed with `FRIGATE_` can also be referenced elsewhere in your configuration using the `{FRIGATE_VARIABLE_NAME}` syntax.
</TabItem>
<TabItem value="yaml">
```yaml
environment_vars:
FRIGATE_MQTT_USER: my_mqtt_user
FRIGATE_MQTT_PASSWORD: my_mqtt_password
mqtt:
host: "{FRIGATE_MQTT_HOST}"
user: "{FRIGATE_MQTT_USER}"
password: "{FRIGATE_MQTT_PASSWORD}"
LIBVA_DRIVER_NAME: i965
```
</TabItem>
@@ -130,6 +118,29 @@ environment_vars:
</TabItem>
</ConfigTabs>
### `secrets.yaml`
A `secrets.yaml` file in your config directory is an additional source of `FRIGATE_` variables, for installs that can't set container environment variables or mount Docker secrets. It's a flat map of names to values, and it is never read or written by the Frigate UI:
```yaml
FRIGATE_CAM_USER: viewer
FRIGATE_CAM_PASS: "p@ss w0rd"
FRIGATE_MQTT_HOST: mqtt.internal.example
```
Names must start with `FRIGATE_`, and nesting is not supported. `secrets.yaml` feeds `{FRIGATE_VARIABLE_NAME}` substitution, so the handful of variables Frigate reads straight from the process environment, such as `FRIGATE_JWT_SECRET`, still need a container environment variable or a Docker secret.
### Substitution sources and precedence
The same `{FRIGATE_VARIABLE_NAME}` placeholder resolves from four sources, listed strongest first. When a name is defined in more than one, the highest wins and a warning is logged:
1. Docker secrets or the directory named by `CREDENTIALS_DIRECTORY` (defaults to `/run/secrets`)
2. Container environment variables
3. `secrets.yaml`
4. The `environment_vars` block above
Referencing a name that no source defines is a config validation error naming the field.
### `database`
Tracked object and recording information is managed in a sqlite database at `/config/frigate.db`. If that database is deleted, recordings will be orphaned and will need to be cleaned up manually. They also won't show up in the Media Browser within Home Assistant.
@@ -177,7 +188,7 @@ Custom models may also require different input tensor formats. The colorspace co
<ConfigTabs>
<TabItem value="ui">
Navigate to <NavPath path="Settings > System > Detectors and model" /> and open the **Custom Model** tab to configure the model path, dimensions, and input format.
Navigate to <NavPath path="Settings > System > Detection models" /> and, on the model you want to change, open the **Custom Model** tab to configure the model path, dimensions, and input format.
| Field | Description |
| --------------------------------------------- | ------------------------------------ |
@@ -192,12 +203,14 @@ Navigate to <NavPath path="Settings > System > Detectors and model" /> and open
```yaml
# Optional: model config
model:
path: /path/to/model
width: 320
height: 320
input_tensor: "nhwc"
input_pixel_format: "bgr"
models:
- devices:
- openvino:GPU
path: /path/to/model
width: 320
height: 320
input_tensor: "nhwc"
input_pixel_format: "bgr"
```
</TabItem>
@@ -214,15 +227,15 @@ If the labelmap is customized then the labels used for alerts will need to be ad
The labelmap can be customized to your needs. A common reason to do this is to combine multiple object types that are easily confused when you don't need to be as granular such as car/truck. By default, truck is renamed to car because they are often confused. You cannot add new object types, but you can change the names of existing objects in the model.
```yaml
model:
labelmap:
2: vehicle
3: vehicle
5: vehicle
7: vehicle
15: animal
16: animal
17: animal
models:
- labelmap:
2: vehicle
3: vehicle
5: vehicle
7: vehicle
15: animal
16: animal
17: animal
```
Note that if you rename objects in the labelmap, you will also need to update your `objects -> track` list as well.
@@ -114,6 +114,30 @@ audio:
</TabItem>
</ConfigTabs>
#### Grouping Audio Labels
Related audio classes can be grouped under one label by mapping their numeric
class IDs to the same name. Add the grouped name to `listen` and use it for any
corresponding filter:
```yaml
audio:
listen:
- dogs
labelmap:
69: dogs # dog
70: dogs # bark
75: dogs # whimper_dog
filters:
dogs:
threshold: 0.8
```
Class IDs are zero-based indices in
[`audio-labelmap.txt`](https://github.com/blakeblackshear/frigate/blob/dev/audio-labelmap.txt),
so each ID is one less than the displayed file line number.
Audio label mappings are separate from the object detector's `model.labelmap`.
### Common Audio Labels
The labelmap includes hundreds of sound types. The labels below are the ones most users may find practical, grouped by what they're typically used for. Use the exact label string from the left column in your `listen` config, or search for the label in the Frigate UI directly.
+23 -16
View File
@@ -18,13 +18,17 @@ Each camera tile in Birdseye is composed from the frames of the stream assigned
## Birdseye Behavior
### Birdseye Modes
### Birdseye Activity Types
Birdseye offers different modes to customize which cameras show under which circumstances.
Birdseye offers independent activity types that control when cameras are shown. Multiple activity types can be listed together.
- **continuous:** All cameras are always included
- **motion:** Cameras that have detected motion within the last 30 seconds are included
- **objects:** Cameras that have tracked an active object within the last 30 seconds are included
- **continuous:** The camera is always included
- **motion:** The camera is included when motion was detected within the last 30 seconds
- **all_objects:** The camera is included when a tracked object is present, active or stationary
- **alerts:** The camera is included while an alert review item is in progress
- **detections:** The camera is included while a detection review item is in progress
`alerts` and `detections` follow the review item's own lifetime, so the camera is removed as soon as the review item ends. Which objects qualify for each is set in [review configuration](./review.md).
### Custom Birdseye Icon
@@ -39,27 +43,29 @@ To include a camera in Birdseye view only for specific circumstances, or exclude
**Global settings:** Navigate to <NavPath path="Settings > System > Birdseye" /> to configure the default Birdseye behavior for all cameras.
**Per-camera overrides:** Navigate to <NavPath path="Settings > Camera configuration > Birdseye" /> to override the mode or disable Birdseye for a specific camera.
**Per-camera overrides:** Navigate to <NavPath path="Settings > Camera configuration > Birdseye" /> to override the activity types or disable Birdseye for a specific camera.
| Field | Description |
| ------------------- | ------------------------------------------------------------- |
| **Enable Birdseye** | Whether this camera appears in Birdseye view |
| **Tracking mode** | When to show the camera: `continuous`, `motion`, or `objects` |
| Field | Description |
| ---------------------- | ---------------------------------------------------------- |
| **Enable Birdseye** | Whether this camera appears in Birdseye view |
| **Activity types** | Conditions that determine when to show the camera |
</TabItem>
<TabItem value="yaml">
```yaml {8-10,12-14}
```yaml {10-12,15-16}
# Include all cameras by default in Birdseye view
birdseye:
enabled: True
mode: continuous
modes:
- continuous
cameras:
front:
# Only include the "front" camera in Birdseye view when objects are detected
# Only include the "front" camera in Birdseye view when an alert is in progress
birdseye:
mode: objects
modes:
- alerts
back:
# Exclude the "back" camera from Birdseye view
birdseye:
@@ -71,7 +77,7 @@ cameras:
### Birdseye Inactivity
By default birdseye shows all cameras that have had the configured activity in the last 30 seconds. This threshold can be configured.
By default birdseye shows all cameras that have had the configured activity in the last 30 seconds. This threshold can be configured, and applies to the `motion` and `all_objects` activity types only.
<ConfigTabs>
<TabItem value="ui">
@@ -140,7 +146,8 @@ Navigate to <NavPath path="Settings > System > Birdseye" /> and in the **Camera
# Include all cameras by default in Birdseye view
birdseye:
enabled: True
mode: continuous
modes:
- continuous
cameras:
front:
+17 -22
View File
@@ -100,7 +100,7 @@ VS Code supports JSON schemas for automatically validating configuration files.
## Environment Variable Substitution
Frigate supports the use of environment variables starting with `FRIGATE_` **only** where specifically indicated in the [reference config](./advanced/reference.md). For example, the following values can be replaced at runtime by using environment variables:
Frigate supports the use of environment variables starting with `FRIGATE_` **only** where specifically indicated in the [reference config](./advanced/reference.md). See [substitution sources and precedence](./advanced/system.md#substitution-sources-and-precedence) for where those values can come from, including `secrets.yaml`. For example, the following values can be replaced at runtime by using environment variables:
```yaml
mqtt:
@@ -154,7 +154,7 @@ Here are some common starter configuration examples. These can be configured thr
1. Navigate to <NavPath path="Settings > System > MQTT" /> and configure the MQTT connection to your Home Assistant Mosquitto broker
2. Navigate to <NavPath path="Settings > Global configuration > FFmpeg" /> and set **Hardware acceleration arguments** to `Raspberry Pi (H.264)`
3. Navigate to <NavPath path="Settings > System > Detectors and model" /> and add a detector with **Type** `EdgeTPU` and **Device** `usb`
3. Navigate to <NavPath path="Settings > System > Detection models" /> and select **Coral EdgeTPU (USB)** from the **Hardware** dropdown
4. Navigate to <NavPath path="Settings > Global configuration > Recording" /> and set **Enable recording** to on, **Motion retention > Retention days** to `7`, **Alert retention > Event retention > Retention days** to `30`, **Alert retention > Event retention > Retention mode** to `motion`, **Detection retention > Event retention > Retention days** to `30`, **Detection retention > Event retention > Retention mode** to `motion`
5. Navigate to <NavPath path="Settings > Global configuration > Snapshots" /> and set **Enable snapshots** to on, **Snapshot retention > Default retention** to `30`
6. Navigate to <NavPath path="Settings > Global configuration > Camera management" /> and add your camera with the appropriate RTSP stream URL
@@ -172,10 +172,9 @@ mqtt:
ffmpeg:
hwaccel_args: preset-rpi-64-h264
detectors:
coral:
type: edgetpu
device: usb
models:
- devices:
- edgetpu:usb
record:
enabled: True
@@ -233,7 +232,7 @@ cameras:
1. Navigate to <NavPath path="Settings > System > MQTT" /> and set **Enable MQTT** to off
2. Navigate to <NavPath path="Settings > Global configuration > FFmpeg" /> and set **Hardware acceleration arguments** to `VAAPI (Intel/AMD GPU)`
3. Navigate to <NavPath path="Settings > System > Detectors and model" /> and add a detector with **Type** `EdgeTPU` and **Device** `usb`
3. Navigate to <NavPath path="Settings > System > Detection models" /> and select **Coral EdgeTPU (USB)** from the **Hardware** dropdown
4. Navigate to <NavPath path="Settings > Global configuration > Recording" /> and set **Enable recording** to on, **Motion retention > Retention days** to `7`, **Alert retention > Event retention > Retention days** to `30`, **Alert retention > Event retention > Retention mode** to `motion`, **Detection retention > Event retention > Retention days** to `30`, **Detection retention > Event retention > Retention mode** to `motion`
5. Navigate to <NavPath path="Settings > Global configuration > Snapshots" /> and set **Enable snapshots** to on, **Snapshot retention > Default retention** to `30`
6. Navigate to <NavPath path="Settings > Global configuration > Camera management" /> and add your camera with the appropriate RTSP stream URL
@@ -249,10 +248,9 @@ mqtt:
ffmpeg:
hwaccel_args: preset-vaapi
detectors:
coral:
type: edgetpu
device: usb
models:
- devices:
- edgetpu:usb
record:
enabled: True
@@ -310,8 +308,8 @@ cameras:
1. Navigate to <NavPath path="Settings > System > MQTT" /> and configure the connection to your MQTT broker
2. Navigate to <NavPath path="Settings > Global configuration > FFmpeg" /> and set **Hardware acceleration arguments** to `VAAPI (Intel/AMD GPU)`
3. Navigate to <NavPath path="Settings > System > Detectors and model" /> and add a detector with **Type** `openvino` and **Device** `AUTO`
4. On the same page, in the **Custom Model** tab, configure the OpenVINO model path and settings
3. Navigate to <NavPath path="Settings > System > Detection models" /> and select **Intel GPU** from the **Hardware** dropdown
4. On the same model, open the **Custom Model** tab and configure the OpenVINO model path and settings
5. Navigate to <NavPath path="Settings > Global configuration > Recording" /> and set **Enable recording** to on, **Motion retention > Retention days** to `7`, **Alert retention > Event retention > Retention days** to `30`, **Alert retention > Event retention > Retention mode** to `motion`, **Detection retention > Event retention > Retention days** to `30`, **Detection retention > Event retention > Retention mode** to `motion`
6. Navigate to <NavPath path="Settings > Global configuration > Snapshots" /> and set **Enable snapshots** to on, **Snapshot retention > Default retention** to `30`
7. Navigate to <NavPath path="Settings > Global configuration > Camera management" /> and add your camera with the appropriate RTSP stream URL
@@ -329,15 +327,12 @@ mqtt:
ffmpeg:
hwaccel_args: preset-vaapi
detectors:
ov:
type: openvino
device: AUTO
model:
width: 300
height: 300
input_tensor: nhwc
models:
- devices:
- openvino:AUTO
width: 300
height: 300
input_tensor: nhwc
input_pixel_format: bgr
path: /openvino-model/ssdlite_mobilenet_v2.xml
labelmap_path: /openvino-model/coco_91cl_bkgr.txt
@@ -106,3 +106,5 @@ Output arguments are passed to FFmpeg after your camera source and control how r
| preset-record-mjpeg | Record - MJPEG Cameras | Record an MJPEG stream | Restreaming the MJPEG stream is recommended instead |
| preset-record-jpeg | Record - JPEG Cameras | Record a live JPEG | Restreaming the live JPEG is recommended instead |
| preset-record-ubiquiti | Record - Ubiquiti Cameras | Record a Ubiquiti stream with audio | Handles Ubiquiti's non-standard audio format |
These presets apply to the `record` output args. If [sub stream recording](/configuration/record#sub-stream-recording) is enabled, the same args are used for the `record_sub` role unless `output_args.record_sub` is set, which accepts the same presets and manual args.
+112 -65
View File
@@ -68,12 +68,66 @@ Frigate supports multiple different detectors that work on different types of ha
:::note
Multiple detectors can not be mixed for object detection (ex: OpenVINO and Coral EdgeTPU can not be used for object detection at the same time).
A single model can not be spread across different detector types (ex: OpenVINO and Coral EdgeTPU can not run the same model at the same time). Configuring more than one model, each on its own detector type, is supported.
This does not affect using hardware for accelerating other tasks such as [semantic search](./semantic_search.md)
:::
### Configuring models and hardware
Object detection is configured with a `models` list. Each entry describes one model and the hardware it runs on:
```yaml
models:
- devices:
- openvino:GPU
path: /config/model_cache/yolov9-s.onnx
model_type: yolo-generic
width: 320
height: 320
```
Each entry in `devices` is a detector type, optionally followed by a colon and a device for that detector, such as `edgetpu:pci:0`, `openvino:NPU`, or `tensorrt:0`. The per-detector sections below document the device values each one accepts. Listing several devices runs the model on all of them, and listing the **same** device more than once runs additional inference processes against it, which can improve throughput on hardware that keeps up with more than one stream:
```yaml
models:
- devices:
- openvino:GPU
- openvino:GPU
```
Coral EdgeTPU and MemryX accelerators can only be opened by one process, so those devices can not be repeated.
### Running more than one model
Cameras can be split across models by scene, which is useful when indoor and outdoor cameras benefit from differently trained models. Each model declares the `scene` it is for, and each camera picks one with `detect -> scene`:
```yaml
models:
- scene: outdoor
path: plus://your-outdoor-model
devices:
- edgetpu:pci:0
- scene: indoor
path: /config/model_cache/indoor.onnx
model_type: yolo-generic
devices:
- openvino:GPU
cameras:
driveway:
detect:
scene: outdoor
...
hallway:
detect:
scene: indoor
...
```
Available scenes are `all`, `indoor`, `outdoor`, `indoor_thermal`, and `outdoor_thermal`. A model with a scene of `all` is used by every camera that does not set one, and `all` is the default when a model does not declare a scene. Changing a camera's scene requires a restart.
### Choosing a model size
Along with picking a detector for your hardware, you will choose a model's **input resolution** (such as `320x320` or `640x640`) and, for model families like YOLOv9, a **variant size** (`tiny`, `small`, etc.). Both affect the balance between accuracy and the inference time your hardware can sustain.
@@ -92,11 +146,11 @@ The best detection accuracy comes from a model trained on images that look like
# Officially Supported Detectors
Frigate provides a number of builtin detector types. By default, Frigate will use a single CPU detector. Other detectors may require additional configuration as described below. When using multiple detectors they will run in dedicated processes, but pull from a common queue of detection requests from across all cameras.
Frigate provides a number of builtin detector types. By default, Frigate will use a single CPU detector. Other detectors may require additional configuration as described below. Each of a model's devices runs in a dedicated process, and they pull from a common queue of detection requests from the cameras assigned to that model.
## Edge TPU Detector
The Edge TPU detector type runs TensorFlow Lite models utilizing the Google Coral delegate for hardware acceleration. To configure an Edge TPU detector, set the `"type"` attribute to `"edgetpu"`.
The Edge TPU detector type runs TensorFlow Lite models utilizing the Google Coral delegate for hardware acceleration. To use it, prefix a model's device with `edgetpu`.
The Edge TPU device can be specified using the `"device"` attribute according to the [Documentation for the TensorFlow Lite Python API](https://coral.ai/docs/edgetpu/multiple-edgetpu/#using-the-tensorflow-lite-python-api). If not set, the delegate will use the first device it finds.
@@ -111,16 +165,15 @@ See [common Edge TPU troubleshooting steps](/troubleshooting/edgetpu) if the Edg
<ConfigTabs>
<TabItem value="ui">
Navigate to <NavPath path="Settings > System > Detectors and model" /> and select **EdgeTPU** from the detector type dropdown and click **Add**, then set device to `usb`.
Navigate to <NavPath path="Settings > System > Detection models" /> and select **Coral EdgeTPU (USB)** from the **Hardware** dropdown.
</TabItem>
<TabItem value="yaml">
```yaml
detectors:
coral:
type: edgetpu
device: usb
models:
- devices:
- edgetpu:usb
```
</TabItem>
@@ -131,19 +184,16 @@ detectors:
<ConfigTabs>
<TabItem value="ui">
Navigate to <NavPath path="Settings > System > Detectors and model" /> and select **EdgeTPU** from the detector type dropdown and click **Add** to add multiple detectors, specifying `usb:0` and `usb:1` as the device for each.
Navigate to <NavPath path="Settings > System > Detection models" /> and select **Coral EdgeTPU (USB)** from the **Hardware** dropdown and check each Coral the model should run on.
</TabItem>
<TabItem value="yaml">
```yaml
detectors:
coral1:
type: edgetpu
device: usb:0
coral2:
type: edgetpu
device: usb:1
models:
- devices:
- edgetpu:usb:0
- edgetpu:usb:1
```
</TabItem>
@@ -156,16 +206,15 @@ _warning: may have [compatibility issues](https://github.com/blakeblackshear/fri
<ConfigTabs>
<TabItem value="ui">
Navigate to <NavPath path="Settings > System > Detectors and model" /> and select **EdgeTPU** from the detector type dropdown and click **Add**, then leave the device field empty.
Navigate to <NavPath path="Settings > System > Detection models" /> and select the **Coral EdgeTPU** entry from the **Hardware** dropdown.
</TabItem>
<TabItem value="yaml">
```yaml
detectors:
coral:
type: edgetpu
device: ""
models:
- devices:
- 'edgetpu:'
```
</TabItem>
@@ -176,16 +225,15 @@ detectors:
<ConfigTabs>
<TabItem value="ui">
Navigate to <NavPath path="Settings > System > Detectors and model" /> and select **EdgeTPU** from the detector type dropdown and click **Add**, then set device to `pci`.
Navigate to <NavPath path="Settings > System > Detection models" /> and select **Coral EdgeTPU (PCIe)** from the **Hardware** dropdown.
</TabItem>
<TabItem value="yaml">
```yaml
detectors:
coral:
type: edgetpu
device: pci
models:
- devices:
- edgetpu:pci
```
</TabItem>
@@ -196,19 +244,16 @@ detectors:
<ConfigTabs>
<TabItem value="ui">
Navigate to <NavPath path="Settings > System > Detectors and model" /> and select **EdgeTPU** from the detector type dropdown and click **Add** to add multiple detectors, specifying `pci:0` and `pci:1` as the device for each.
Navigate to <NavPath path="Settings > System > Detection models" /> and select **Coral EdgeTPU (PCIe)** from the **Hardware** dropdown and check each Coral the model should run on.
</TabItem>
<TabItem value="yaml">
```yaml
detectors:
coral1:
type: edgetpu
device: pci:0
coral2:
type: edgetpu
device: pci:1
models:
- devices:
- edgetpu:pci:0
- edgetpu:pci:1
```
</TabItem>
@@ -219,19 +264,16 @@ detectors:
<ConfigTabs>
<TabItem value="ui">
Navigate to <NavPath path="Settings > System > Detectors and model" /> and select **EdgeTPU** from the detector type dropdown and click **Add** to add multiple detectors with different device types (e.g., `usb` and `pci`).
Navigate to <NavPath path="Settings > System > Detection models" /> and select **Coral EdgeTPU (USB)** from the **Hardware** dropdown. USB and PCIe Corals are listed as separate hardware, so mixing the two on one model has to be done in YAML.
</TabItem>
<TabItem value="yaml">
```yaml
detectors:
coral_usb:
type: edgetpu
device: usb
coral_pci:
type: edgetpu
device: pci
models:
- devices:
- edgetpu:usb
- edgetpu:pci
```
</TabItem>
@@ -273,7 +315,7 @@ Hailo8 supports all models in the Hailo Model Zoo that include HailoRT post-proc
## OpenVINO Detector
The OpenVINO detector type runs an OpenVINO IR model on AMD and Intel CPUs, Intel GPUs and Intel NPUs. To configure an OpenVINO detector, set the `"type"` attribute to `"openvino"`.
The OpenVINO detector type runs an OpenVINO IR model on AMD and Intel CPUs, Intel GPUs and Intel NPUs. To use it, prefix a model's device with `openvino`.
The OpenVINO device to be used is specified using the `"device"` attribute according to the naming conventions in the [Device Documentation](https://docs.openvino.ai/2025/openvino-workflow/running-inference/inference-devices-and-modes.html). The most common devices are `CPU`, `GPU`, or `NPU`.
@@ -286,13 +328,10 @@ OpenVINO is supported on 6th Gen Intel platforms (Skylake) and newer. It will al
When using many cameras one detector may not be enough to keep up. Multiple detectors can be defined assuming GPU resources are available. An example configuration would be:
```yaml
detectors:
ov_0:
type: openvino
device: GPU # or NPU
ov_1:
type: openvino
device: GPU # or NPU
models:
- devices:
- openvino:GPU # or NPU
- openvino:GPU # or NPU
```
:::
@@ -313,6 +352,12 @@ Intel NPUs cannot be used under Home Assistant OS, which does not include the NP
## Apple Silicon detector
:::warning
The network-based detectors (Deepstack and the Apple Silicon client) are being reworked. Their extra options no longer have a place in the config, so only the endpoint carried in the device string is honored right now: Deepstack ignores `api_key` and `api_timeout`, and the Apple Silicon client ignores `request_timeout_ms` and `linger_ms`. Anything else is dropped when your config is migrated.
:::
The NPU in Apple Silicon can't be accessed from within a container, so the [Apple Silicon detector client](https://github.com/frigate-nvr/apple-silicon-detector) must first be setup. It is recommended to use the Frigate docker image with `-standard-arm64` suffix, for example `ghcr.io/blakeblackshear/frigate:stable-standard-arm64`.
### Setup {#setup-apple-silicon}
@@ -453,11 +498,10 @@ If the correct build is used for your GPU then the GPU will be detected and used
When using many cameras one detector may not be enough to keep up. Multiple detectors can be defined assuming GPU resources are available. An example configuration would be:
```yaml
detectors:
onnx_0:
type: onnx
onnx_1:
type: onnx
models:
- devices:
- onnx
- onnx
```
:::
@@ -470,7 +514,7 @@ detectors:
## CPU Detector (not recommended)
The CPU detector type runs a TensorFlow Lite model utilizing the CPU without hardware acceleration. It is recommended to use a hardware accelerated detector type instead for better performance. To configure a CPU based detector, set the `"type"` attribute to `"cpu"`.
The CPU detector type runs a TensorFlow Lite model utilizing the CPU without hardware acceleration. It is recommended to use a hardware accelerated detector type instead for better performance. To use it, set a model's device to `cpu`.
:::danger
@@ -480,7 +524,7 @@ The CPU detector is not recommended for general use. If you do not have GPU or E
The number of threads used by the interpreter can be specified using the `"num_threads"` attribute, and defaults to `3.`
A TensorFlow Lite model is provided in the container at `/cpu_model.tflite` and is used by this detector type by default. To provide your own model, bind mount the file into the container and provide the path with `model.path`.
A TensorFlow Lite model is provided in the container at `/cpu_model.tflite` and is used by this detector type by default. To provide your own model, bind mount the file into the container and provide the path with the model's `path`.
### Configuration {#configuration-cpu}
@@ -490,6 +534,12 @@ When using CPU detectors, you can add one CPU detector per camera. Adding more d
## Deepstack / CodeProject.AI Server Detector
:::warning
The network-based detectors (Deepstack and the Apple Silicon client) are being reworked. Their extra options no longer have a place in the config, so only the endpoint carried in the device string is honored right now: Deepstack ignores `api_key` and `api_timeout`, and the Apple Silicon client ignores `request_timeout_ms` and `linger_ms`. Anything else is dropped when your config is migrated.
:::
The Deepstack / CodeProject.AI Server detector for Frigate allows you to integrate Deepstack and CodeProject.AI object detection capabilities into Frigate. CodeProject.AI and DeepStack are open-source AI platforms that can be run on various devices such as the Raspberry Pi, Nvidia Jetson, and other compatible hardware. It is important to note that the integration is performed over the network, so the inference times may not be as fast as native Frigate detectors, but it still provides an efficient and reliable solution for object detection and tracking.
### Setup {#setup-deepstack}
@@ -552,7 +602,7 @@ For detailed instructions on compiling models, refer to the [MemryX Compiler](ht
3. Depending on the model, the compiler may also generate a cropped post-processing network. If present, it will be named with the suffix `_post.onnx`.
4. Bind-mount the `.zip` file into the container and specify its path using `model.path` in your config.
4. Bind-mount the `.zip` file into the container and specify its path using the model's `path` in your config.
5. Update `labelmap_path` to match your custom model's labels.
@@ -682,13 +732,10 @@ If no custom model is provided, the RKNN detector downloads a default model from
When using many cameras one detector may not be enough to keep up. Multiple detectors can be defined assuming NPU resources are available. An example configuration would be:
```yaml
detectors:
rknn_0:
type: rknn
num_cores: 0
rknn_1:
type: rknn
num_cores: 0
models:
- devices:
- rknn:0
- rknn:0
```
:::
+157
View File
@@ -275,6 +275,163 @@ record:
This configuration will retain recording segments that overlap with alerts and detections for 10 days. Because multiple tracked objects can reference the same recording segments, this avoids storing duplicate footage for overlapping tracked objects and reduces overall storage needs.
## Sub Stream Recording
In addition to the main recording stream, Frigate can record a second, lower quality stream for each camera. This serves two purposes:
- **Quality selection during playback**: A quality selector (`Auto`, `Original`, or `Low`) appears in History view for cameras with sub stream recording enabled. `Original` and `Low` play only that stream's recordings. Time ranges where the selected stream has no footage are skipped during playback, and the selector notes when the selected stream has no recordings at all in the viewed time range. With `Auto` (the default), playback prefers the original quality and automatically falls back to the low quality stream when the connection cannot keep up, or for time ranges where the original recordings have expired. The selector shows each stream's video codec and audio details beneath the options; footage recorded by older Frigate versions shows no details.
- **Extended retention**: Sub stream recordings have their own retention settings, fully independent of the main recordings. By giving the low quality recordings a longer retention period, you can keep weeks or months of low quality history using a fraction of the storage, and that history remains playable after the main recordings expire. Playback falls back to the low quality recordings automatically, and the timeline shows a muted treatment for time ranges where only low quality footage remains.
### Configuring sub stream recording
Sub stream recording uses the `record_sub` input role. This role can be assigned to the same input as `detect`, so in the common case where detect already uses the camera's sub stream, no additional camera connection is needed. Like the main recording stream, sub stream segments are copied directly from the camera stream without re-encoding, so the recording quality is determined by the source stream.
The following examples keep 7 days of full quality continuous recordings and 60 days of low quality continuous recordings:
<ConfigTabs>
<TabItem value="ui">
Navigate to <NavPath path="Settings > Camera configuration > Streams (FFmpeg)" /> and select the camera.
- In **Camera inputs**, enable the **Record (Sub Stream)** role on the stream you want to record at low quality, commonly the same stream that has the **Detect** role. Only one stream may have this role, and it cannot be assigned to the same stream as the **Record** role.
Navigate to <NavPath path="Settings > Camera configuration > Recording" /> and select the camera.
- Set **Enable recording** to on
- Set **Continuous retention > Retention days** to `7`
- Set **Sub stream recording > Enable sub stream recording** to on
- Set **Sub stream recording > Sub stream continuous retention > Retention days** to `60`
The camera setup wizard also offers the **Record (Sub Stream)** role when assigning stream roles for a newly added camera.
</TabItem>
<TabItem value="yaml">
```yaml
cameras:
front_door:
ffmpeg:
inputs:
- path: rtsp://camera/main
roles:
- record
- path: rtsp://camera/sub
roles:
- detect
- record_sub
record:
enabled: true
continuous:
days: 7
sub:
enabled: true
continuous:
days: 60
```
If your camera does not provide a suitable sub stream (or the sub stream is already used at a resolution you don't want to record), you can use a go2rtc transcode as the source for `record_sub` instead:
```yaml
go2rtc:
streams:
front_door: rtsp://camera/main
front_door_lq: ffmpeg:front_door#video=h264#width=854#hardware
cameras:
front_door:
ffmpeg:
inputs:
- path: rtsp://127.0.0.1:8554/front_door
input_args: preset-rtsp-restream
roles:
- detect
- record
- path: rtsp://127.0.0.1:8554/front_door_lq
input_args: preset-rtsp-restream
roles:
- record_sub
record:
enabled: true
continuous:
days: 7
sub:
enabled: true
continuous:
days: 60
```
</TabItem>
</ConfigTabs>
The `record.sub` config supports the same retention structure as the main recording config: `continuous`, `motion`, `alerts`, and `detections` each with their own `days` (and `mode` for alerts and detections). The pre-capture and post-capture windows for alerts and detections are taken from the main `record.alerts` and `record.detections` config. Extending `sub.alerts.days` or `sub.detections.days` beyond the main values also keeps those review items visible in the review timeline for the longer window, with playback falling back to the low quality stream once the main recordings expire.
:::note
Recording must be enabled (`record.enabled`) for sub stream recording to run, and Frigate will fail to start if `record.sub.enabled` is set without a `record_sub` role assigned to one of the camera's inputs.
:::
### How Auto picks a quality
`Auto` measures throughput on every segment download and compares it against the original stream's bitrate (computed from the recorded footage itself). Playback drops to the low quality stream when any of these happen:
- A freeze lasts 4 seconds (10 seconds when it starts within 2 seconds of a seek, since the seek target is rarely buffered), or freezes total 7 seconds within the last minute.
- 3 downloads in a row measure below the original bitrate plus 10%, dropping quality before a stall ever becomes visible.
- No first frame appears within 10 seconds, or loading fails outright.
Playback returns to full quality only when measured throughput exceeds the original bitrate by 50%, checked continuously while playing the low quality stream and again at each new hour. The asymmetric thresholds (1.1x to drop, 1.5x to return) keep a borderline connection from switching back and forth.
The most recent measurement is remembered on the device: a connection last measured below the original bitrate (or below 3 Mbps when the bitrate is not yet known) starts playback on the low quality stream so a first frame appears immediately, then upgrades within a few segments if the speed allows.
The quality selector shows which stream Auto is currently playing and why. A browser with Data Saver enabled stays on the low quality stream, a browser that cannot decode the original stream's codec (for example H.265 without HEVC support) plays the low quality stream for that camera, and pinning `Original` or `Low` bypasses Auto entirely.
### Sub stream output args
By default the sub stream is recorded with the same [output args](/configuration/ffmpeg_presets#output-args-presets) as the main recording stream, so it inherits any customization made to `ffmpeg.output_args.record`. Setting `ffmpeg.output_args.record_sub` gives the sub stream its own args instead. Like all `ffmpeg` config, this can be set globally or per camera.
The most common reason to set this is a pair of streams whose audio differs. Many cameras send AAC on the main stream but PCM on the sub stream, and PCM cannot be copied into an mp4 recording. Copying the main stream's audio avoids re-encoding audio that is already AAC, while the sub stream still needs to be transcoded:
```yaml
ffmpeg:
output_args:
# main stream audio is already AAC, so copy it
record: preset-record-generic-audio-copy
# sub stream audio is PCM, so transcode it to AAC
record_sub: preset-record-generic-audio-aac
```
Other reasons to set this are recording a sub stream whose codec needs a different preset than the main stream, such as `preset-record-mjpeg`, or forcing a matching audio sample rate across the two streams with manual args ending in `-c:a aac -ar 16000`.
:::warning
Avoid removing audio from only one of the two streams (for example with `-an`). When one stream has audio and the other does not, playback of time ranges that combine both qualities is silent, so stripping audio from the sub stream also silences the merged timeline.
:::
### Which stream do features use?
As a general rule, features that read recordings prefer the main stream and fall back to the sub stream for time ranges where the main recordings have expired. Analytics features use only the main stream.
| Feature | Stream used |
| ---------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------- |
| Recording playback (History and Review) | Both (main preferred with sub fallback by default), or exactly one stream when a quality is selected manually |
| Tracking details and Explore clip playback | Main, falling back to sub where the main recordings have expired |
| Exports and clip downloads | Main; sub is used when no main recordings remain in the range (streams are never mixed in one file) |
| Frames grabbed from a recording in History (download snapshot, submit frame to Frigate+) | Main preferred, sub fallback |
| Audio extraction (e.g., transcription) | Main preferred, sub fallback |
| Motion search | Main only |
| Review timeline motion data | Main only |
| Storage usage statistics | Both streams counted, and listed separately per camera |
This table covers only features that read recordings from disk. Tracked object snapshots and thumbnails (the images shown in Explore and sent with notifications, and the images submitted to Frigate+ from a tracked object) are captured live from the `detect` stream as the object is tracked, never from recordings, so sub stream recording does not affect them.
### Trade-offs
- Recording a second stream increases overall storage use. The increase is typically small relative to the main recordings, since the low quality stream is much smaller.
- The go2rtc transcode approach continuously encodes the low quality stream, which uses CPU or GPU resources. This cost only applies to the transcode path; recording the camera's native sub stream does not re-encode. See the [go2rtc hardware acceleration documentation](https://github.com/AlexxIT/go2rtc?tab=readme-ov-file#source-ffmpeg) for accelerating the transcode.
- Many camera sub streams do not include audio. If the source stream has no audio, the low quality recordings will not have audio.
- **Matching video codecs and audio settings between the two streams gives the smoothest playback.** When playback combines both qualities on one timeline (the default `Auto` behavior: for example original quality during events with low quality in between, or low quality history after the original recordings expire) and the streams use different video codecs or audio settings, for example H.265 on the main stream and H.264 on the sub stream, or 16 kHz audio on one and 8 kHz on the other, playback still works: Frigate inserts a decoder reset at each quality transition, which can cause a barely-perceptible pause there. Configuring both streams in the camera's firmware to use the same video codec, audio codec, and sample rate makes transitions fully seamless, and a mismatched audio sample rate can also be corrected with [sub stream output args](#sub-stream-output-args). If one stream has audio and the other does not, combined time ranges play **without audio**; selecting a single quality with the playback selector always keeps that stream's audio.
## Can I have "continuous" recordings, but only at certain times?
Using Frigate UI, Home Assistant, or MQTT, cameras can be automated to only record in certain situations or at certain times.
+1 -1
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@@ -221,7 +221,7 @@ For security reasons, the `echo:`, `expr:`, and `exec:` stream sources are disab
If you attempt to use these sources in your configuration, the streams will be removed and an error message will be printed in the logs.
To enable these sources, you must set the environment variable `GO2RTC_ALLOW_ARBITRARY_EXEC=true`. This can be done in your Docker Compose file or container environment:
To enable these sources, you must set the environment variable `GO2RTC_ALLOW_ARBITRARY_EXEC=true`. This can be done in your Docker Compose file or container environment, or for Home Assistant App users with the `go2rtc_allow_arbitrary_exec` option in the App's configuration. The `environment_vars` section of the Frigate config can't enable it:
```yaml
environment:
+2
View File
@@ -612,6 +612,8 @@ Home Assistant OS users can install via the App repository.
5. Start the App
6. Use the _Open Web UI_ button to access the Frigate UI, then click in the _cog icon_ > _Configuration editor_ and configure Frigate to your liking
App users who can't set container environment variables can put `FRIGATE_` values in a `secrets.yaml` in the config directory instead. See [`secrets.yaml`](../configuration/advanced/system.md#secretsyaml).
There are several variants of the App available:
| App Variant | Description |
+16 -21
View File
@@ -204,8 +204,8 @@ You need to refer to **Configure hardware acceleration** above to enable the con
<ConfigTabs>
<TabItem value="ui">
1. Navigate to <NavPath path="Settings > System > Detectors and model" /> and add a detector with **Type** `OpenVINO` and **Device** `GPU`
2. On the same page, in the **Custom Model** tab, configure the model settings for OpenVINO:
1. Navigate to <NavPath path="Settings > System > Detection models" /> and select **Intel GPU** from the **Hardware** dropdown
2. On the same model, open the **Custom Model** tab and configure the model settings for OpenVINO:
| Field | Value |
| ---------------------------------------- | ------------------------------------------ |
@@ -222,15 +222,12 @@ You need to refer to **Configure hardware acceleration** above to enable the con
```yaml {3-6,9-15,20-21}
mqtt: ...
detectors: # <---- add detectors
ov:
type: openvino # <---- use openvino detector
device: GPU
# We will use the default MobileNet_v2 model from OpenVINO.
model:
width: 300
height: 300
models: # <---- add models
- devices:
- openvino:GPU # <---- use the openvino detector on the GPU
# We will use the default MobileNet_v2 model from OpenVINO.
width: 300
height: 300
input_tensor: nhwc
input_pixel_format: bgr
path: /openvino-model/ssdlite_mobilenet_v2.xml
@@ -273,7 +270,7 @@ services:
<ConfigTabs>
<TabItem value="ui">
Navigate to <NavPath path="Settings > System > Detectors and model" /> and add a detector with **Type** `EdgeTPU` and **Device** `usb`.
Navigate to <NavPath path="Settings > System > Detection models" /> and select **Coral EdgeTPU (USB)** from the **Hardware** dropdown.
</TabItem>
<TabItem value="yaml">
@@ -281,10 +278,9 @@ Navigate to <NavPath path="Settings > System > Detectors and model" /> and add a
```yaml {3-6,11-12}
mqtt: ...
detectors: # <---- add detectors
coral:
type: edgetpu
device: usb
models: # <---- add models
- devices:
- edgetpu:usb
cameras:
name_of_your_camera:
@@ -321,10 +317,9 @@ If you are using YAML to configure Frigate instead of the UI, your configuration
mqtt:
enabled: False
detectors:
coral:
type: edgetpu
device: usb
models:
- devices:
- edgetpu:usb
cameras:
name_of_your_camera:
@@ -357,7 +352,7 @@ In order to review activity in the Frigate UI, recordings need to be enabled.
```yaml {16-17}
mqtt: ...
detectors: ...
models: ...
cameras:
name_of_your_camera:
+13 -10
View File
@@ -553,22 +553,25 @@ must be enabled in the configuration.
Topic with current state of Birdseye for a camera. Published values are `ON` and `OFF`.
### `frigate/<camera_name>/birdseye_mode/set`
### `frigate/<camera_name>/birdseye_modes/set`
Topic to set Birdseye mode for a camera. Birdseye offers different modes to customize under which circumstances the camera is shown.
Topic to set the Birdseye activity types for a camera. Send one uppercase activity type or combine multiple types with commas, for example `MOTION,ALERTS`.
_Note: Changing the value from `CONTINUOUS` -> `MOTION | OBJECTS` will take up to 30 seconds for
_Note: Changing the value from `CONTINUOUS` to non-continuous activity types will take up to 30 seconds for
the camera to be removed from the view._
| Command | Description |
| ------------ | ----------------------------------------------------------------- |
| `CONTINUOUS` | Always included |
| `MOTION` | Show when detected motion within the last 30 seconds are included |
| `OBJECTS` | Shown if an active object tracked within the last 30 seconds |
| Command | Description |
| ------------- | ---------------------------------------------------------------- |
| `CONTINUOUS` | Always included |
| `MOTION` | Shown if motion was detected within the last 30 seconds |
| `ALL_OBJECTS` | Shown if a tracked object was present within the last 30 seconds |
| `ALERTS` | Shown while an alert review item is in progress |
| `DETECTIONS` | Shown while a detection review item is in progress |
| `NONE` | Never included |
### `frigate/<camera_name>/birdseye_mode/state`
### `frigate/<camera_name>/birdseye_modes/state`
Topic with current state of the Birdseye mode for a camera. Published values are `CONTINUOUS`, `MOTION`, `OBJECTS`.
Topic with the current Birdseye activity types for a camera. Multiple enabled types are published as a comma-separated value in the order `CONTINUOUS`, `MOTION`, `ALL_OBJECTS`, `ALERTS`, `DETECTIONS`. `NONE` is published when no activity types are enabled.
### `frigate/<camera_name>/notifications/set`
+11 -11
View File
@@ -59,13 +59,12 @@ You can view all of your submitted images at [https://plus.frigate.video](https:
Once you have [requested your first model](../plus/first_model.md) and gotten your own model ID, it can be used with a special model path. No other information needs to be configured for Frigate+ models because it fetches the remaining config from Frigate+ automatically.
You can either choose the new model from the <NavPath path="Settings > System > Detectors and model" /> pane in the Frigate UI (the **Frigate+ Model** tab), or manually set the model at the root level in your config:
You can either choose the new model from the <NavPath path="Settings > System > Detection models" /> pane in the Frigate UI (on the **Frigate+** tab of the model you want to change), or set it on that model in your config:
```yaml
detectors: ...
model:
path: plus://<your_model_id>
models:
- devices: ...
path: plus://<your_model_id>
```
:::note
@@ -79,10 +78,11 @@ Models are downloaded into the `/config/model_cache` folder and only downloaded
If needed, you can override the labelmap for Frigate+ models. This is not recommended as renaming labels will break the Submit to Frigate+ feature if the labels are not available in Frigate+.
```yaml
model:
path: plus://<your_model_id>
labelmap:
3: animal
4: animal
5: animal
models:
- devices: ...
path: plus://<your_model_id>
labelmap:
3: animal
4: animal
5: animal
```
+4 -5
View File
@@ -30,16 +30,15 @@ Models available in Frigate+ can be used with a special model path. No other inf
<ConfigTabs>
<TabItem value="ui">
Navigate to <NavPath path="Settings > System > Detectors and model" />. In the **Detection Model** section, choose the **Frigate+** tab. Select your new Frigate+ model from the **Available Frigate+ models** dropdown, then click **Save**. Restart Frigate to apply the change.
Navigate to <NavPath path="Settings > System > Detection models" />. On the model you want to change, choose the **Frigate+** tab and select your new Frigate+ model from the **Available Frigate+ models** dropdown, then click **Save**. Restart Frigate to apply the change.
</TabItem>
<TabItem value="yaml">
```yaml
detectors: ...
model:
path: plus://<your_model_id>
models:
- devices: ...
path: plus://<your_model_id>
```
:::tip
+1 -1
View File
@@ -131,7 +131,7 @@ The process was killed by the CPU for executing an unsupported instruction. Ther
<FaqItem id="onnx-invalidprotobuf" question="ONNX Runtime InvalidProtobuf / failed to load model">
ONNX Runtime could not parse the model file. The file exists but its contents are not a valid ONNX model, usually a corrupted or interrupted download in `model_cache`, or the wrong file pointed at by `model.path`. Delete the cached model file so Frigate re-downloads it, and confirm `model.path` points at an actual `.onnx` model. See [ONNX detector configuration](/configuration/object_detectors#onnx).
ONNX Runtime could not parse the model file. The file exists but its contents are not a valid ONNX model, usually a corrupted or interrupted download in `model_cache`, or the wrong file pointed at by a model's `path`. Delete the cached model file so Frigate re-downloads it, and confirm the model's `path` points at an actual `.onnx` model. See [ONNX detector configuration](/configuration/object_detectors#onnx).
</FaqItem>
+2 -2
View File
@@ -40,7 +40,7 @@ Deleting a group also clears any custom layout you saved for it.
## Rearranging a camera group layout
On desktop and tablet, each camera group has its own freely-arrangeable grid. Enter **Edit Layout** mode from the layout button in the lower-right corner: camera tiles gain a drag handle and corner resize handles. Drag a tile to reposition it and drag a corner to resize it (the aspect ratio is preserved). Exit edit mode to save. The layout is stored in your browser per device, so each device can have its own arrangement.
On desktop and tablet, each camera group has its own freely-arrangeable grid. Enter **Edit Layout** mode from the layout button in the lower-right corner: camera tiles gain a drag handle and corner resize handles. Drag a tile to reposition it and drag a corner to resize it (the aspect ratio is preserved). Exit edit mode to save. The layout is stored in your browser per device, so each device can have its own arrangement, and layouts can be exported to a file and imported on another device.
The default **All Cameras** dashboard is not manually arrangeable. It automatically sizes tiles based on each camera's aspect ratio (wide cameras span two columns, tall cameras span two rows).
@@ -68,7 +68,7 @@ For non-default groups, the context menu also exposes **Streaming Settings** for
- the **streaming method**: **No Streaming**, **Smart Streaming** (recommended), or **Continuous Streaming** (higher bandwidth), and
- **compatibility mode**, for devices that have trouble rendering the default player.
These settings are saved per group and per device in your browser, not in your config file.
These settings are saved per group and per device in your browser, not in your config file, and can be exported to a file and imported on another device.
## The single-camera view
+1 -2
View File
@@ -63,8 +63,7 @@ SYSTEM_NAV: dict[str, tuple[str, str]] = {
"environment_vars": ("System", "Environment variables"),
"telemetry": ("System", "Telemetry"),
"birdseye": ("System", "Birdseye"),
"detectors": ("System", "Detectors and model"),
"model": ("System", "Detectors and model"),
"models": ("System", "Detection models"),
}
# All known top-level config section keys
+273 -7
View File
@@ -713,7 +713,7 @@ paths:
| `improve_contrast` | `ON`, `OFF` |
| `ptz_autotracker` | `ON`, `OFF` |
| `birdseye` | `ON`, `OFF` |
| `birdseye_mode` | `CONTINUOUS`, `MOTION`, `OBJECTS` |
| `birdseye_modes` | `CONTINUOUS`, `MOTION`, `ALL_OBJECTS`, `ALERTS`, `DETECTIONS`, `NONE`, or a comma-separated combination |
| `motion_contour_area` | integer |
| `motion_threshold` | integer |
| `motion_mask` | `ON`, `OFF` |
@@ -803,7 +803,7 @@ paths:
| `improve_contrast` | `ON`, `OFF` |
| `ptz_autotracker` | `ON`, `OFF` |
| `birdseye` | `ON`, `OFF` |
| `birdseye_mode` | `CONTINUOUS`, `MOTION`, `OBJECTS` |
| `birdseye_modes` | `CONTINUOUS`, `MOTION`, `ALL_OBJECTS`, `ALERTS`, `DETECTIONS`, `NONE`, or a comma-separated combination |
| `motion_contour_area` | integer |
| `motion_threshold` | integer |
| `motion_mask` | `ON`, `OFF` |
@@ -2308,15 +2308,15 @@ paths:
$ref: '#/components/schemas/HTTPValidationError'
security:
- frigateUserAuth: []
x-required-role: any
description: '**Access:** Any authenticated user.'
x-required-role: camera
description: '**Access:** Authenticated user with access to the referenced camera.'
/review/summarize/start/{start_ts}/end/{end_ts}:
post:
tags:
- Review
summary: Generate Review Summary
description: |-
**Access:** Admin role required.
**Access:** Authenticated user with access to all cameras.
Use GenAI to summarize review items over a period of time.
operationId:
@@ -2347,8 +2347,8 @@ paths:
schema:
$ref: '#/components/schemas/HTTPValidationError'
security:
- frigateAdminAuth: []
x-required-role: admin
- frigateUserAuth: []
x-required-role: all_cameras
/:
get:
tags:
@@ -2946,6 +2946,44 @@ paths:
- frigateUserAuth: []
x-required-role: any
description: '**Access:** Any authenticated user.'
/categorized_object_names:
get:
tags:
- App
summary: Get known object names by object type
description: |-
**Access:** Any authenticated user.
Returns the sub labels and attributes this install can attach,
grouped by object type. Unlike /sub_labels, which reflects what has already been
detected, this reads the config and model files, so it covers recognized face
names, named license plates, custom object classification categories, and the
detector attributes of tracked objects.
operationId: categorized_object_names_categorized_object_names_get
parameters:
- name: object_type
in: query
required: false
schema:
anyOf:
- type: string
- type: 'null'
title: Object Type
responses:
'200':
description: Successful Response
content:
application/json:
schema: {}
'422':
description: Validation Error
content:
application/json:
schema:
$ref: '#/components/schemas/HTTPValidationError'
security:
- frigateUserAuth: []
x-required-role: any
/audio_labels:
get:
tags:
@@ -3972,6 +4010,49 @@ paths:
security:
- frigateAdminAuth: []
x-required-role: admin
/hardware/probe:
get:
tags:
- Hardware
summary: Probe Hardware
description: |-
**Access:** Admin role required.
Get the object detection hardware attached to this system.
Args:
refresh: Probe again instead of returning the cached result
Returns:
Every kind of detection hardware that was found
operationId: probe_hardware_hardware_probe_get
parameters:
- name: refresh
in: query
required: false
schema:
type: boolean
default: false
title: Refresh
responses:
'200':
description: Successful Response
content:
application/json:
schema:
type: array
items:
$ref: '#/components/schemas/DetectionHardware'
title: Response Probe Hardware Hardware Probe Get
'422':
description: Validation Error
content:
application/json:
schema:
$ref: '#/components/schemas/HTTPValidationError'
security:
- frigateAdminAuth: []
x-required-role: admin
/events:
get:
tags:
@@ -5984,6 +6065,65 @@ paths:
security:
- frigateUserAuth: []
x-required-role: camera
/vod/{camera_name}/{stream}/start/{start_ts}/end/{end_ts}:
get:
tags:
- Media
summary: Vod Ts Stream
description: |-
**Access:** Authenticated user with access to the referenced camera.
Returns an HLS playlist pinned to one stream type (main or sub) for the specified timestamp-range on the specified camera. Append /master.m3u8 or /index.m3u8 for HLS playback.
operationId:
vod_ts_stream_vod__camera_name___stream__start__start_ts__end__end_ts__get
parameters:
- name: camera_name
in: path
required: true
schema:
anyOf:
- type: string
- type: 'null'
title: Camera Name
- name: stream
in: path
required: true
schema:
$ref: '#/components/schemas/VodStreamPreference'
- name: start_ts
in: path
required: true
schema:
type: number
title: Start Ts
- name: end_ts
in: path
required: true
schema:
type: number
title: End Ts
- name: force_discontinuity
in: query
required: false
schema:
type: boolean
default: false
title: Force Discontinuity
responses:
'200':
description: Successful Response
content:
application/json:
schema: {}
'422':
description: Validation Error
content:
application/json:
schema:
$ref: '#/components/schemas/HTTPValidationError'
security:
- frigateUserAuth: []
x-required-role: camera
/events/{event_id}/snapshot.jpg:
get:
tags:
@@ -6922,6 +7062,63 @@ paths:
security:
- frigateUserAuth: []
x-required-role: camera
/{camera_name}/recordings/coverage:
get:
tags:
- Recordings
summary: Recordings Coverage
description: |-
**Access:** Authenticated user with access to the referenced camera.
Returns merged recording coverage spans plus codec compatibility.
codecs_compatible is false only when more than one known video codec
appears across the range's rows, the case where the merged vod route
degrades to a single-stream manifest.
operationId: recordings_coverage__camera_name__recordings_coverage_get
parameters:
- name: camera_name
in: path
required: true
schema:
anyOf:
- type: string
- type: 'null'
title: Camera Name
- name: after
in: query
required: true
schema:
type: number
title: After
- name: before
in: query
required: true
schema:
type: number
title: Before
- name: timelines
in: query
required: false
schema:
type: boolean
default: false
title: Timelines
responses:
'200':
description: Successful Response
content:
application/json:
schema: {}
'422':
description: Validation Error
content:
application/json:
schema:
$ref: '#/components/schemas/HTTPValidationError'
security:
- frigateUserAuth: []
x-required-role: camera
/{camera_name}/recordings:
get:
tags:
@@ -7688,6 +7885,46 @@ components:
required:
- ids
title: DeleteFaceImagesBody
DetectionHardware:
properties:
key:
type: string
title: Hardware key
description: Stable identifier for this kind of hardware.
detector:
type: string
title: Detector type
description: The detector that drives this hardware.
name:
type: string
title: Hardware name
description: Human readable name for this kind of hardware.
units:
items:
$ref: '#/components/schemas/HardwareUnit'
type: array
title: Units
description: Each physical piece of this hardware that was found.
count:
type: integer
title: Unit count
description: How many units were found.
unlimited:
type: boolean
title: Unlimited detectors
description: Whether this hardware can run more inference processes
than there are units.
type: object
required:
- key
- detector
- name
- units
- count
- unlimited
title: DetectionHardware
description: A kind of detection hardware, and every unit of it that was
found.
EventCreateResponse:
properties:
success:
@@ -8415,6 +8652,24 @@ components:
title: Detail
type: object
title: HTTPValidationError
HardwareUnit:
properties:
device:
type: string
title: Device string
description: The value to put in a model's devices list, for example
'edgetpu:pci:1'.
label:
type: string
title: Unit label
description: How to identify this unit among others of the same kind,
for example 'PCIe 1'.
type: object
required:
- device
- label
title: HardwareUnit
description: One physical piece of hardware.
Last24HoursReview:
properties:
reviewed_alert:
@@ -8905,6 +9160,17 @@ components:
- msg
- type
title: ValidationError
VodStreamPreference:
type: string
enum:
- main
- sub
title: VodStreamPreference
description: |-
Stream pin for the path-segment VOD route.
nginx-vod derives its mapping fetch URI from the playlist URL path
(query params are dropped), so the preference must be a path segment.
securitySchemes:
frigateAdminAuth:
type: apiKey
+58 -29
View File
@@ -71,6 +71,7 @@ from frigate.util.config import (
find_config_file,
redact_credential,
)
from frigate.util.object_names import get_categorized_object_names
from frigate.util.schema import get_config_schema
from frigate.util.services import (
get_nvidia_driver_info,
@@ -291,10 +292,6 @@ def config(request: Request):
config: dict[str, dict[str, Any]] = config_obj.model_dump(
mode="json", warnings="none", exclude_none=True
)
config["detectors"] = {
name: detector.model_dump(mode="json", warnings="none", exclude_none=True)
for name, detector in config_obj.detectors.items()
}
# remove environment_vars for non-admin users
if request.headers.get("remote-role") != "admin":
@@ -375,31 +372,28 @@ def config(request: Request):
config["go2rtc"]["streams"][stream_name] = cleaned
config["plus"] = {"enabled": request.app.frigate_config.plus_api.is_active()}
config["model"]["colormap"] = config_obj.model.colormap
config["model"]["all_attributes"] = config_obj.model.all_attributes
config["model"]["non_logo_attributes"] = config_obj.model.non_logo_attributes
# Add model plus data if plus is enabled
if config["plus"]["enabled"]:
model_path = config.get("model", {}).get("path")
if model_path:
model_json_path = FilePath(model_path).with_suffix(".json")
for index, model in enumerate(config_obj.models):
model_dict = config["models"][index]
model_dict["colormap"] = model.colormap
model_dict["all_attributes"] = model.all_attributes
model_dict["non_logo_attributes"] = model.non_logo_attributes
model_dict["labelmap"] = model.merged_labelmap
if not config["plus"]["enabled"]:
continue
# Add model plus data if plus is enabled
model_dict["plus"] = None
if model.path:
model_json_path = FilePath(model.path).with_suffix(".json")
try:
with open(model_json_path) as f:
model_plus_data = json.load(f)
config["model"]["plus"] = model_plus_data
except FileNotFoundError:
config["model"]["plus"] = None
except json.JSONDecodeError:
config["model"]["plus"] = None
else:
config["model"]["plus"] = None
# use merged labelamp
for detector_config in config["detectors"].values():
detector_config["model"]["labelmap"] = (
request.app.frigate_config.model.merged_labelmap
)
model_dict["plus"] = json.load(f)
except (FileNotFoundError, json.JSONDecodeError):
pass
return JSONResponse(content=config)
@@ -1313,9 +1307,41 @@ def get_sub_labels(
return JSONResponse(content=sub_labels)
@router.get(
"/categorized_object_names",
dependencies=[Depends(allow_any_authenticated())],
summary="Get known object names by object type",
description="""Returns the sub labels and attributes this install can attach,
grouped by object type. Unlike /sub_labels, which reflects what has already been
detected, this reads the config and model files, so it covers recognized face
names, named license plates, custom object classification categories, and the
detector attributes of tracked objects.""",
)
def categorized_object_names(
request: Request,
object_type: str | None = None,
allowed_cameras: list[str] = Depends(get_allowed_cameras_for_filter),
):
return JSONResponse(
content=get_categorized_object_names(
request.app.frigate_config, allowed_cameras, object_type
)
)
@router.get("/audio_labels", dependencies=[Depends(allow_any_authenticated())])
def get_audio_labels():
def get_audio_labels(request: Request):
labels = load_labels("/audio-labelmap.txt", prefill=521)
# configured overrides group several audio classes under one label, and the
# detector merges them over the defaults at runtime. Offer them here too, or
# a grouped label could never be picked in the UI.
config: FrigateConfig = request.app.frigate_config
labels.update(config.audio.labelmap)
for camera in config.cameras.values():
labels.update(camera.audio.labelmap)
return JSONResponse(content=labels)
@@ -1337,11 +1363,14 @@ def plusModels(request: Request, filterByCurrentModelDetector: bool = False):
modelList = models["list"]
config: FrigateConfig = request.app.frigate_config
primary_model = config.primary_model
# current model type
modelType = request.app.frigate_config.model.model_type
modelType = primary_model.model_type
# current detectorType for comparing to supportedDetectors
detectorType = list(request.app.frigate_config.detectors.values())[0].type
detectorType = config.devices_for_model(primary_model)[0].detector
validModels = []
+26 -3
View File
@@ -83,6 +83,7 @@ def require_admin_by_default():
"/nvinfo",
"/labels",
"/sub_labels",
"/categorized_object_names",
"/plus/models",
"/recognized_license_plates",
"/timeline",
@@ -971,6 +972,7 @@ def delete_user(request: Request, username: str):
summary="Update user password",
description="Updates a user's password. Users can only change their own password unless they have admin role. Requires the current password to verify identity for non-admin users. Password must be at least 12 characters long. If user changes their own password, a new JWT cookie is automatically issued.",
)
@limiter.limit(limit_value=rateLimiter.get_limit)
async def update_password(
request: Request,
username: str,
@@ -984,10 +986,11 @@ async def update_password(
current_username = current_user.get("username")
current_role = current_user.get("role")
# viewers can only change their own password
if current_role == "viewer" and current_username != username:
# Only admins may target another account. This has to cover every non-admin
# role rather than just viewer, since custom roles are arbitrary names
if current_role != "admin" and current_username != username:
raise HTTPException(
status_code=403, detail="Viewers can only update their own password"
status_code=403, detail="Users can only update their own password"
)
HASH_ITERATIONS = request.app.frigate_config.auth.hash_iterations
@@ -1251,3 +1254,23 @@ async def get_allowed_cameras_for_filter(request: Request):
all_camera_names = set(request.app.frigate_config.cameras.keys())
roles_dict = request.app.frigate_config.auth.roles
return User.get_allowed_cameras(role, roles_dict, all_camera_names)
async def require_full_camera_access(
request: Request,
allowed_cameras: list[str] = Depends(get_allowed_cameras_for_filter),
):
"""Dependency for endpoints returning data that spans every camera.
Some responses cannot be meaningfully scoped to a subset of cameras, so
rather than filter them the endpoint is limited to callers who can already
see every camera. Admin and viewer always qualify; a custom role qualifies
only when its camera list covers all configured cameras.
"""
all_camera_names = set(request.app.frigate_config.cameras.keys())
if not all_camera_names.issubset(allowed_cameras):
raise HTTPException(
status_code=403,
detail="Access to all cameras is required for this endpoint",
)
+40 -3
View File
@@ -33,7 +33,7 @@ from frigate.config.camera.updater import (
CameraConfigUpdateEnum,
CameraConfigUpdateTopic,
)
from frigate.config.env import substitute_frigate_vars
from frigate.config.env import UnknownVariableError, substitute_frigate_vars
from frigate.models import User
from frigate.util.builtin import clean_camera_user_pass, get_record_segment_time
from frigate.util.camera_cleanup import cleanup_camera_db, cleanup_camera_files
@@ -166,7 +166,7 @@ def go2rtc_add_stream(request: Request, stream_name: str, src: str = ""):
if src:
try:
resolved_src = substitute_frigate_vars(src)
except KeyError:
except UnknownVariableError:
resolved_src = src
if is_restricted_go2rtc_source(resolved_src):
@@ -651,6 +651,32 @@ async def _connect_onvif_camera(
raise first_error
def _supports_continuous_pan_tilt(nodes) -> bool:
"""Whether any PTZ node advertises continuous pan/tilt velocity.
The web UI's directional controls issue ContinuousMove with a PanTilt
velocity, so continuous pan/tilt is what makes those controls usable. This
is intentionally narrower than ptz_supported, which is true for any device
exposing the ONVIF PTZ service - including zoom/focus-only varifocal lenses.
"""
for node in nodes or []:
spaces = getattr(node, "SupportedPTZSpaces", None) or (
node.get("SupportedPTZSpaces") if isinstance(node, dict) else None
)
if spaces is None:
continue
continuous = getattr(spaces, "ContinuousPanTiltVelocitySpace", None) or (
spaces.get("ContinuousPanTiltVelocitySpace")
if isinstance(spaces, dict)
else None
)
if continuous:
return True
return False
@router.get(
"/onvif/probe",
dependencies=[Depends(require_role(["admin"]))],
@@ -808,6 +834,7 @@ async def onvif_probe(
# Check PTZ support and capabilities
ptz_supported = False
pan_tilt_supported = False
presets_count = 0
autotrack_supported = False
@@ -841,6 +868,15 @@ async def onvif_probe(
logger.debug(f"Failed to get presets: {e}")
presets_count = 0
# Check for real (continuous) pan/tilt, which the UI controls need
if ptz_supported:
try:
nodes = await ptz_service.GetNodes()
pan_tilt_supported = _supports_continuous_pan_tilt(nodes)
logger.debug(f"Continuous pan/tilt supported: {pan_tilt_supported}")
except Exception as e:
logger.debug(f"Failed to read PTZ nodes for pan/tilt support: {e}")
# Check for autotracking support - requires both FOV relative movement and MoveStatus
if ptz_supported and first_profile_token and ptz_config_token:
# First check for FOV relative movement support
@@ -960,6 +996,7 @@ async def onvif_probe(
"firmware_version": device_info["firmware_version"],
"profiles_count": profiles_count,
"ptz_supported": ptz_supported,
"pan_tilt_supported": pan_tilt_supported,
"presets_count": presets_count,
"autotrack_supported": autotrack_supported,
}
@@ -1349,7 +1386,7 @@ def camera_set(
| `improve_contrast` | `ON`, `OFF` |
| `ptz_autotracker` | `ON`, `OFF` |
| `birdseye` | `ON`, `OFF` |
| `birdseye_mode` | `CONTINUOUS`, `MOTION`, `OBJECTS` |
| `birdseye_modes` | `CONTINUOUS`, `MOTION`, `ALL_OBJECTS`, `ALERTS`, `DETECTIONS`, `NONE`, or a comma-separated combination |
| `motion_contour_area` | integer |
| `motion_threshold` | integer |
| `motion_mask` | `ON`, `OFF` |
+27 -4
View File
@@ -50,6 +50,7 @@ from frigate.jobs.vlm_watch import (
stop_vlm_watch_job,
)
from frigate.models import Event
from frigate.util.object_names import get_categorized_object_names
logger = logging.getLogger(__name__)
@@ -539,6 +540,11 @@ async def execute_tool(
if tool_name == "search_objects":
return await _execute_search_objects(request, arguments, allowed_cameras)
if tool_name == "get_categorized_object_names":
return JSONResponse(
content=_execute_get_categorized_object_names(request, allowed_cameras)
)
if tool_name == "find_similar_objects":
result = await _execute_find_similar_objects(
request, arguments, allowed_cameras
@@ -591,7 +597,7 @@ async def _execute_get_live_context(
try:
frame_processor = request.app.detected_frames_processor
camera_state = frame_processor.camera_states.get(camera)
camera_state = frame_processor.get_camera_state(camera)
if camera_state is None:
return {
@@ -655,7 +661,7 @@ async def _get_live_frame_image_url(
return None
try:
frame_processor = request.app.detected_frames_processor
if camera not in frame_processor.camera_states:
if frame_processor.get_camera_state(camera) is None:
return None
frame = frame_processor.get_current_frame(camera, {})
if frame is None:
@@ -717,6 +723,21 @@ async def _execute_set_camera_state(
return {"success": True, "camera": camera, "feature": feature, "value": value}
def _execute_get_categorized_object_names(
request: Request,
allowed_cameras: list[str],
) -> dict[str, Any]:
names = get_categorized_object_names(request.app.frigate_config, allowed_cameras)
if not names:
return {
"names": {},
"message": "No names configured; search by label or semantic_query.",
}
return {"names": names}
async def _execute_tool_internal(
tool_name: str,
arguments: dict[str, Any],
@@ -741,6 +762,8 @@ async def _execute_tool_internal(
except (json.JSONDecodeError, AttributeError) as e:
logger.warning(f"Failed to extract tool result: {e}")
return {"error": "Failed to parse tool result"}
elif tool_name == "get_categorized_object_names":
return _execute_get_categorized_object_names(request, allowed_cameras)
elif tool_name == "find_similar_objects":
return await _execute_find_similar_objects(request, arguments, allowed_cameras)
elif tool_name == "set_camera_state":
@@ -773,8 +796,8 @@ async def _execute_tool_internal(
else:
logger.error(
"Tool call failed: unknown tool %r. Expected one of: search_objects, find_similar_objects, "
"get_live_context, start_camera_watch, stop_camera_watch, get_profile_status, get_recap. "
"Arguments received: %s",
"get_categorized_object_names, get_live_context, start_camera_watch, stop_camera_watch, "
"get_profile_status, get_recap. Arguments received: %s",
tool_name,
json.dumps(arguments),
)
+1
View File
@@ -8,6 +8,7 @@ class Tags(Enum):
chat = "Chat"
events = "Events"
export = "Export"
hardware = "Hardware"
classification = "Classification"
logs = "Logs"
media = "Media"
+2 -2
View File
@@ -1313,7 +1313,7 @@ async def set_sub_label(
if request.app.detected_frames_processor:
tracked_obj: TrackedObject = None
for state in request.app.detected_frames_processor.camera_states.values():
for state in request.app.detected_frames_processor.get_camera_states():
tracked_obj = state.tracked_objects.get(event_id)
if tracked_obj is not None:
@@ -1372,7 +1372,7 @@ async def set_plate(
if request.app.detected_frames_processor:
tracked_obj: TrackedObject = None
for state in request.app.detected_frames_processor.camera_states.values():
for state in request.app.detected_frames_processor.get_camera_states():
tracked_obj = state.tracked_objects.get(event_id)
if tracked_obj is not None:
+2
View File
@@ -21,6 +21,7 @@ from frigate.api import (
debug_replay,
event,
export,
hardware,
media,
motion_search,
notification,
@@ -145,6 +146,7 @@ def create_fastapi_app(
app.include_router(preview.router)
app.include_router(notification.router)
app.include_router(export.router)
app.include_router(hardware.router)
app.include_router(event.router)
app.include_router(media.router)
app.include_router(motion_search.router)
+30
View File
@@ -0,0 +1,30 @@
"""Hardware discovery APIs."""
import logging
from fastapi import APIRouter, Depends
from frigate.api.auth import require_role
from frigate.api.defs.tags import Tags
from frigate.detectors.hardware import DetectionHardware, hardware_prober
logger = logging.getLogger(__name__)
router = APIRouter(tags=[Tags.hardware])
@router.get(
"/hardware/probe",
response_model=list[DetectionHardware],
dependencies=[Depends(require_role(["admin"]))],
)
def probe_hardware(refresh: bool = False) -> list[DetectionHardware]:
"""Get the object detection hardware attached to this system.
Args:
refresh: Probe again instead of returning the cached result
Returns:
Every kind of detection hardware that was found
"""
return hardware_prober.probe(refresh=refresh)
+317 -152
View File
@@ -6,10 +6,13 @@ import logging
import math
import os
import subprocess as sp
import tempfile
import time
from collections.abc import Iterator
from datetime import UTC, datetime, timedelta
from enum import Enum
from pathlib import Path as FilePath
from typing import Any
from typing import IO, Any
from urllib.parse import unquote
import cv2
@@ -39,12 +42,14 @@ from frigate.config.camera.snapshots import SnapshotsConfig
from frigate.const import (
CACHE_DIR,
INSTALL_DIR,
MAX_SEGMENT_DURATION,
PREVIEW_FRAME_TYPE,
STREAM_TYPE_MAIN,
STREAM_TYPE_SUB,
)
from frigate.models import Event, Previews, Recordings, Regions, ReviewSegment
from frigate.output.preview import get_most_recent_preview_frame
from frigate.track.object_processing import TrackedObjectProcessor
from frigate.util.ffmpeg import terminate_ffmpeg_stream
from frigate.util.file import (
get_event_snapshot_bytes,
get_event_snapshot_path,
@@ -52,12 +57,40 @@ from frigate.util.file import (
load_event_snapshot_image,
)
from frigate.util.image import get_image_from_recording, get_image_quality_params
from frigate.util.media import get_keyframe_before
from frigate.util.object import create_empty_regions_grid
from frigate.util.recording_coverage import (
build_spans,
null_audio_glitches,
plan_clip,
resolve_coverage,
stream_has_audio,
)
logger = logging.getLogger(__name__)
# must match the patched MAX_CLIPS in docker/main/build_nginx.sh; a
# normal hour needs ~360, one clip per recording file
NGINX_VOD_MAX_CLIPS = 1080
# tail of ffmpeg's stderr kept for the clip download failure log
CLIP_STDERR_LOG_BYTES = 8192
# how long a drained clip download waits for ffmpeg to exit on its own
CLIP_FFMPEG_EXIT_TIMEOUT = 10
class VodStreamPreference(str, Enum):
"""Stream pin for the path-segment VOD route.
nginx-vod derives its mapping fetch URI from the playlist URL path
(query params are dropped), so the preference must be a path segment.
"""
main = STREAM_TYPE_MAIN
sub = STREAM_TYPE_SUB
router = APIRouter(tags=[Tags.media])
@@ -319,7 +352,7 @@ async def get_snapshot_from_recording(
& (frame_time <= Recordings.end_time)
)
.where(Recordings.camera == camera_name)
.order_by(Recordings.start_time.desc())
.order_by(Recordings.stream_type.asc(), Recordings.start_time.desc())
.limit(1)
.get()
)
@@ -338,7 +371,7 @@ async def get_snapshot_from_recording(
& (frame_time <= Recordings.end_time)
)
.where(Recordings.camera == camera_name)
.order_by(Recordings.start_time.desc())
.order_by(Recordings.stream_type.asc(), Recordings.start_time.desc())
.limit(1)
.get()
)
@@ -398,7 +431,7 @@ async def submit_recording_snapshot_to_plus(
(frame_time >= Recordings.start_time) & (frame_time <= Recordings.end_time)
)
.where(Recordings.camera == camera_name)
.order_by(Recordings.start_time.desc())
.order_by(Recordings.stream_type.asc(), Recordings.start_time.desc())
.limit(1)
)
@@ -441,6 +474,53 @@ async def submit_recording_snapshot_to_plus(
)
def _read_stderr_tail(stderr_file: IO[bytes]) -> str:
"""Read back the last CLIP_STDERR_LOG_BYTES of a captured stderr file."""
stderr_file.seek(0, os.SEEK_END)
stderr_file.seek(max(0, stderr_file.tell() - CLIP_STDERR_LOG_BYTES))
return stderr_file.read().decode("utf-8", "replace")
def _run_clip_download(ffmpeg_cmd: list[str], file_path: str) -> Iterator[bytes]:
"""Stream an ffmpeg concat remux to the client, always cleaning up after it."""
stderr_file = None
ffmpeg = None
try:
stderr_file = tempfile.TemporaryFile()
ffmpeg = sp.Popen(ffmpeg_cmd, stdout=sp.PIPE, stderr=stderr_file)
while True:
data = ffmpeg.stdout.read(8192)
if not data:
break
yield data
try:
# wait rather than signal, so the real exit code survives
ffmpeg.wait(timeout=CLIP_FFMPEG_EXIT_TIMEOUT)
except sp.TimeoutExpired:
pass
finally:
if ffmpeg is not None:
# read before terminating: a None here is our teardown, not a failure
exit_code = ffmpeg.poll()
terminate_ffmpeg_stream(ffmpeg)
if exit_code:
logger.error(
"Failed to generate clip, ffmpeg logs: %s",
_read_stderr_tail(stderr_file),
)
if stderr_file is not None:
stderr_file.close()
FilePath(file_path).unlink(missing_ok=True)
@router.get(
"/{camera_name}/start/{start_ts}/end/{end_ts}/clip.mp4",
dependencies=[Depends(require_camera_access)],
@@ -452,40 +532,29 @@ async def recording_clip(
start_ts: float,
end_ts: float,
):
def run_download(ffmpeg_cmd: list[str], file_path: str):
with sp.Popen(
ffmpeg_cmd,
stderr=sp.PIPE,
stdout=sp.PIPE,
text=False,
) as ffmpeg:
while True:
data = ffmpeg.stdout.read(8192)
if data is not None and len(data) > 0:
yield data
else:
if ffmpeg.returncode and ffmpeg.returncode != 0:
logger.error(
f"Failed to generate clip, ffmpeg logs: {ffmpeg.stderr.read()}"
)
else:
FilePath(file_path).unlink(missing_ok=True)
break
def get_clip_query(stream_type: str):
return (
Recordings.select(
Recordings.path,
Recordings.start_time,
Recordings.end_time,
)
.where(
(Recordings.start_time.between(start_ts, end_ts))
| (Recordings.end_time.between(start_ts, end_ts))
| ((start_ts > Recordings.start_time) & (end_ts < Recordings.end_time))
)
.where(Recordings.camera == camera_name)
.where(Recordings.stream_type == stream_type)
.order_by(Recordings.start_time.asc())
)
recordings = (
Recordings.select(
Recordings.path,
Recordings.start_time,
Recordings.end_time,
)
.where(
(Recordings.start_time.between(start_ts, end_ts))
| (Recordings.end_time.between(start_ts, end_ts))
| ((start_ts > Recordings.start_time) & (end_ts < Recordings.end_time))
)
.where(Recordings.camera == camera_name)
.order_by(Recordings.start_time.asc())
)
# never mix streams in one concat; use main when available and
# fall back to sub for expired-main history
recordings = get_clip_query(STREAM_TYPE_MAIN)
if recordings.count() == 0:
recordings = get_clip_query(STREAM_TYPE_SUB)
if recordings.count() == 0:
return JSONResponse(
@@ -496,7 +565,9 @@ async def recording_clip(
status_code=400,
)
file_name = sanitize_filename(f"playlist_{camera_name}_{start_ts}-{end_ts}.txt")
file_name = sanitize_filename(
f"playlist_{camera_name}_{start_ts}-{end_ts}_{os.urandom(4).hex()}.txt"
)
file_path = os.path.join(CACHE_DIR, file_name)
with open(file_path, "w") as file:
clip: Recordings
@@ -544,22 +615,65 @@ async def recording_clip(
]
return StreamingResponse(
run_download(ffmpeg_cmd, file_path),
_run_clip_download(ffmpeg_cmd, file_path),
media_type="video/mp4",
)
@router.get(
"/vod/{camera_name}/start/{start_ts}/end/{end_ts}",
dependencies=[Depends(require_camera_access)],
description="Returns an HLS playlist for the specified timestamp-range on the specified camera. Append /master.m3u8 or /index.m3u8 for HLS playback.",
)
async def vod_ts(
def _build_vod_clip(
row: Any, start: float, end: float
) -> tuple[dict[str, Any], int] | None:
"""Build one nginx-vod clip dict + duration (ms) for a recording row trimmed to [start, end).
Realization comes entirely from the shared plan_clip, so the coverage
endpoint's realized timelines match this manifest by construction.
"""
plan = plan_clip(row, start, end)
if plan.skipped:
return None
clip: dict[str, Any] = {"type": "source", "path": row.path}
if plan.clip_from_ms is not None:
clip["clipFrom"] = plan.clip_from_ms
if plan.key_frame_durations is not None:
# real gaps enable keyframe-aligned sub-file segments (bootstrap
# ladder); the whole-clip fallback keeps one segment per file,
# the only safe cut without an index
if plan.first_key_frame_offset_ms > 0:
clip["firstKeyFrameOffset"] = plan.first_key_frame_offset_ms
clip["keyFrameDurations"] = plan.key_frame_durations
else:
clip["keyFrameDurations"] = [plan.duration_ms]
logger.debug(
"VOD: added clip %s duration_ms=%s clipFrom=%s",
row.path,
plan.duration_ms,
clip.get("clipFrom"),
)
return clip, plan.duration_ms
async def _vod_response(
camera_name: str,
start_ts: float,
end_ts: float,
force_discontinuity: bool = False,
):
stream_preference: str | None = None,
) -> JSONResponse:
"""Build an nginx-vod mapping JSON for a camera over a timestamp range.
Always a single-sequence mapping; quality selection happens in the
frontend by choosing between this route and the stream-pinned routes.
Args:
camera_name: The camera to build the mapping for
start_ts: Range start as a unix timestamp
end_ts: Range end as a unix timestamp
force_discontinuity: Emit HLS discontinuity markers between clips
stream_preference: Pin the manifest to one stream type ("main" or
"sub"), serving only that stream's recordings
"""
logger.debug(
"VOD: Generating VOD for %s from %s to %s with force_discontinuity=%s",
camera_name,
@@ -567,104 +681,85 @@ async def vod_ts(
end_ts,
force_discontinuity,
)
recordings = (
Recordings.select(
Recordings.path,
Recordings.duration,
Recordings.end_time,
Recordings.start_time,
)
.where(
Recordings.start_time.between(start_ts, end_ts)
| Recordings.end_time.between(start_ts, end_ts)
| ((start_ts > Recordings.start_time) & (end_ts < Recordings.end_time))
)
.where(Recordings.camera == camera_name)
.order_by(Recordings.start_time.asc())
.iterator()
intervals = resolve_coverage(camera_name, start_ts, end_ts)
# rows contradicting their stream's audio composition are
# truncated-shutdown glitches
main_audio = stream_has_audio(intervals, main=True)
sub_audio = stream_has_audio(intervals, main=False)
spans = build_spans(
null_audio_glitches(intervals, main_audio, sub_audio),
stream_preference,
)
clips = []
durations = []
min_duration_ms = 100 # Minimum 100ms to ensure at least one video frame
max_duration_ms = MAX_SEGMENT_DURATION * 1000
recording: Recordings
for recording in recordings:
durations: list[int] = []
clips: list[dict[str, Any]] = []
# gathered after glitch-nulling and span building, so the policy
# decisions below reflect the manifest's real contents
video_codecs: set[str] = set()
audio_presence: set[bool] = set()
audio_params: set[tuple[str | None, int | None]] = set()
span_streams: set[bool] = set()
for row, span_start, span_end, span_is_main in spans:
logger.debug(
"VOD: processing recording: %s start=%s end=%s duration=%s",
recording.path,
recording.start_time,
recording.end_time,
recording.duration,
row.path,
row.start_time,
row.end_time,
row.duration,
)
built = _build_vod_clip(row, span_start, span_end)
clip = {"type": "source", "path": recording.path}
duration = int(recording.duration * 1000)
# adjust start offset if start_ts is after recording.start_time
if start_ts > recording.start_time:
inpoint = int((start_ts - recording.start_time) * 1000)
clip["clipFrom"] = inpoint
duration -= inpoint
logger.debug(
"VOD: applied clipFrom %sms to %s",
inpoint,
recording.path,
)
# adjust end if recording.end_time is after end_ts
if recording.end_time > end_ts:
duration -= int((recording.end_time - end_ts) * 1000)
# nginx-vod-module pushes clipFrom forward to the next keyframe,
# which can leave too few frames and produce an empty/unplayable
# segment. Snap clipFrom back to the preceding keyframe so the
# segment always starts with a decodable frame.
if "clipFrom" in clip:
keyframe_ms = get_keyframe_before(recording.path, clip["clipFrom"])
if keyframe_ms is not None:
gained = clip["clipFrom"] - keyframe_ms
clip["clipFrom"] = keyframe_ms
duration += gained
logger.debug(
"VOD: snapped clipFrom to keyframe at %sms for %s, duration now %sms",
keyframe_ms,
recording.path,
duration,
)
else:
# could not read keyframes, remove clipFrom to use full recording
logger.debug(
"VOD: no keyframe info for %s, removing clipFrom to use full recording",
recording.path,
)
del clip["clipFrom"]
duration = int(recording.duration * 1000)
if recording.end_time > end_ts:
duration -= int((recording.end_time - end_ts) * 1000)
if duration < min_duration_ms:
# skip if the clip has no valid duration (too short to contain frames)
logger.debug(
"VOD: skipping recording %s - resulting duration %sms too short",
recording.path,
duration,
)
if built is None:
continue
if min_duration_ms <= duration < max_duration_ms:
clip["keyFrameDurations"] = [duration]
clips.append(clip)
durations.append(duration)
logger.debug(
"VOD: added clip %s duration_ms=%s clipFrom=%s",
recording.path,
duration,
clip.get("clipFrom"),
)
else:
logger.warning(f"Recording clip is missing or empty: {recording.path}")
clips.append(built[0])
durations.append(built[1])
span_streams.add(span_is_main)
if row.video_codec is not None:
video_codecs.add(row.video_codec)
audio_presence.add(row.has_audio is not False)
# legacy rows contribute no signature, so uniformly-unknown
# history keeps the legacy shape
if row.has_audio is not False and (
row.audio_codec is not None or row.audio_rate is not None
):
audio_params.add((row.audio_codec, row.audio_rate))
# nginx-vod requires a uniform track count per sequence, and adding or
# removing an audio track across an MSE discontinuity is unproven
if len(audio_presence) > 1:
logger.debug(
"VOD: %s mixes audio-bearing and audio-less recordings between "
"%s and %s; serving the range without audio",
camera_name,
start_ts,
end_ts,
)
for clip in clips:
clip["tracks"] = "v"
# discontinuity mode emits per-clip init segments, letting the decoder
# reconfigure at each boundary. Stream type counts as a signature of
# its own: the two encoders differ in SPS/PPS even when codec name and
# audio params match, and a single-init manifest then decode-fails on
# players that only configure from the init segment (iOS)
use_discontinuity = (
len(video_codecs) > 1 or len(audio_params) > 1 or len(span_streams) > 1
)
if use_discontinuity:
logger.debug(
"VOD: %s mixes media signatures between %s and %s (video codecs "
"%s, audio params %s, streams %s); serving a discontinuity "
"manifest with per-clip init segments",
camera_name,
start_ts,
end_ts,
sorted(video_codecs),
sorted(audio_params, key=str),
sorted(span_streams),
)
if not clips:
logger.error(
@@ -678,16 +773,50 @@ async def vod_ts(
status_code=404,
)
if len(clips) > NGINX_VOD_MAX_CLIPS:
logger.warning(
"VOD: %s needs %d clips between %s and %s, exceeding nginx's "
"limit of %d; playback of this range will fail. This usually "
"means the camera produced abnormally short recording segments "
"(check the stream's timestamps)",
camera_name,
len(clips),
start_ts,
end_ts,
NGINX_VOD_MAX_CLIPS,
)
# segmentation comes from the vod_* nginx directives plus per-clip
# keyFrameDurations; a segment_duration field here was always ignored
# (nginx-vod parses only camelCase segmentDuration)
hour_ago = datetime.now() - timedelta(hours=1)
return JSONResponse(
content={
"cache": hour_ago.timestamp() > start_ts,
"discontinuity": force_discontinuity,
"consistentSequenceMediaInfo": True,
"durations": durations,
"segment_duration": max(durations),
"sequences": [{"clips": clips}],
}
content = {
"cache": hour_ago.timestamp() > start_ts,
"discontinuity": force_discontinuity or use_discontinuity,
"consistentSequenceMediaInfo": True,
"durations": durations,
"sequences": [{"clips": clips}],
}
if use_discontinuity:
# clip-indexed naming is what makes nginx-vod emit per-clip
# EXT-X-MAP outside of its live mode
content["initialClipIndex"] = 1
return JSONResponse(content=content)
@router.get(
"/vod/{camera_name}/start/{start_ts}/end/{end_ts}",
dependencies=[Depends(require_camera_access)],
description="Returns an HLS playlist for the specified timestamp-range on the specified camera. Append /master.m3u8 or /index.m3u8 for HLS playback.",
)
async def vod_ts(
camera_name: str,
start_ts: float,
end_ts: float,
force_discontinuity: bool = False,
):
return await _vod_response(
camera_name, start_ts, end_ts, force_discontinuity=force_discontinuity
)
@@ -776,7 +905,43 @@ async def vod_clip(
start_ts: float,
end_ts: float,
):
return await vod_ts(camera_name, start_ts, end_ts, force_discontinuity=True)
# the tracking-details player corrects its timeline from
# sequences[0].clips[0].clipFrom
return await _vod_response(
camera_name,
start_ts,
end_ts,
force_discontinuity=True,
)
# registered after /vod/clip/... on purpose: both routes are six path
# segments, Starlette matches structurally in registration order, and the
# enum validation on {stream} would otherwise 422 every /vod/clip request
@router.get(
"/vod/{camera_name}/{stream}/start/{start_ts}/end/{end_ts}",
dependencies=[Depends(require_camera_access)],
description="Returns an HLS playlist pinned to one stream type (main or sub) for the specified timestamp-range on the specified camera. Append /master.m3u8 or /index.m3u8 for HLS playback.",
)
async def vod_ts_stream(
camera_name: str,
stream: VodStreamPreference,
start_ts: float,
end_ts: float,
force_discontinuity: bool = False,
):
"""VOD for a timestamp range pinned to one stream type.
How the frontend selects quality, now that mappings are always
single-sequence.
"""
return await _vod_response(
camera_name,
start_ts,
end_ts,
force_discontinuity=force_discontinuity,
stream_preference=stream.value,
)
@router.get(
@@ -814,13 +979,13 @@ async def event_snapshot(
timestamp_style=request.app.frigate_config.cameras[
event.camera
].timestamp_style,
colormap=request.app.frigate_config.model.colormap,
colormap=request.app.frigate_config.model_for_camera(event.camera).colormap,
)
except DoesNotExist:
# see if the object is currently being tracked
try:
camera_states: list[CameraState] = (
request.app.detected_frames_processor.camera_states.values()
request.app.detected_frames_processor.get_camera_states()
)
for camera_state in camera_states:
if event_id in camera_state.tracked_objects:
@@ -898,7 +1063,7 @@ async def event_thumbnail(
if thumbnail_bytes is None:
# see if the object is currently being tracked
try:
camera_states = request.app.detected_frames_processor.camera_states.values()
camera_states = request.app.detected_frames_processor.get_camera_states()
for camera_state in camera_states:
if event_id in camera_state.tracked_objects:
tracked_obj = camera_state.tracked_objects.get(event_id)
@@ -1127,7 +1292,7 @@ async def event_snapshot_clean(request: Request, event_id: str, download: bool =
# see if the object is currently being tracked
try:
camera_states = (
request.app.detected_frames_processor.camera_states.values()
request.app.detected_frames_processor.get_camera_states()
)
for camera_state in camera_states:
if event_id in camera_state.tracked_objects:
+102
View File
@@ -1,8 +1,10 @@
"""Notification apis."""
import ipaddress
import logging
import os
from typing import Any
from urllib.parse import urlparse
from cryptography.hazmat.primitives import serialization
from fastapi import APIRouter, Depends, Request
@@ -19,6 +21,95 @@ logger = logging.getLogger(__name__)
router = APIRouter(tags=[Tags.notifications])
# Push endpoints are opaque URLs but stay well under this in practice
MAX_ENDPOINT_LENGTH = 2048
# Suffixes that only ever resolve on the local network
INTERNAL_HOST_SUFFIXES = (".local", ".localdomain", ".internal", ".home.arpa")
def _validate_push_endpoint(endpoint: Any) -> str | None:
"""Return a reason the endpoint is unusable, or None when it is valid.
Subscriptions are issued by the browser vendor's push service, so a valid
endpoint is always a public https URL. Anything else is either a broken
registration or an attempt to aim the notification sender somewhere it
should not reach.
"""
if not isinstance(endpoint, str) or not endpoint:
return "endpoint must be a url"
if len(endpoint) > MAX_ENDPOINT_LENGTH:
return "endpoint is too long"
try:
parsed = urlparse(endpoint)
port = parsed.port
except ValueError:
return "endpoint is not a valid url"
if parsed.scheme != "https":
return "endpoint must use https"
if parsed.username or parsed.password:
return "endpoint must not include credentials"
if port is not None and port != 443:
return "endpoint must use the default https port"
hostname = parsed.hostname
if not hostname:
return "endpoint must include a hostname"
try:
address = ipaddress.ip_address(hostname)
except ValueError:
address = None
if address is not None:
# A push service is never reachable at an address only this network can
# route, so anything non-global is a misconfiguration at best
if not address.is_global:
return "endpoint must not use a private address"
elif hostname == "localhost" or "." not in hostname:
return "endpoint must use a fully qualified hostname"
elif hostname.endswith(INTERNAL_HOST_SUFFIXES):
return "endpoint must not use an internal hostname"
# The subscription token lives in the path, and webpush.py assumes there is
# a separator after the host when it builds the VAPID audience
if len(parsed.path) <= 1:
return "endpoint must include a subscription path"
return None
def _validate_subscription(sub: Any) -> str | None:
"""Return a reason the subscription is unusable, or None when it is valid."""
if not isinstance(sub, dict):
return "subscription must be an object"
reason = _validate_push_endpoint(sub.get("endpoint"))
if reason:
return reason
keys = sub.get("keys")
if not isinstance(keys, dict):
return "subscription must include keys"
# WebPusher raises on a missing key, which would break every send for the
# user rather than just this registration
for name in ("p256dh", "auth"):
value = keys.get(name)
if not isinstance(value, str) or not value:
return f"subscription keys must include {name}"
return None
@router.get(
"/notifications/pubkey",
@@ -71,6 +162,17 @@ def register_notifications(request: Request, body: dict = None):
status_code=400,
)
reason = _validate_subscription(sub)
if reason:
logger.warning(
"Rejected notification registration for %s: %s", username, reason
)
return JSONResponse(
content={"success": False, "message": f"Invalid subscription: {reason}"},
status_code=400,
)
try:
User.update(notification_tokens=User.notification_tokens.append(sub)).where(
User.username == username
+190 -56
View File
@@ -25,8 +25,20 @@ from frigate.api.defs.query.recordings_query_parameters import (
)
from frigate.api.defs.response.generic_response import GenericResponse
from frigate.api.defs.tags import Tags
from frigate.const import RECORD_DIR
from frigate.const import (
MAX_SEGMENT_DURATION,
RECORD_DIR,
STREAM_TYPE_MAIN,
STREAM_TYPE_SUB,
)
from frigate.models import Event, Recordings
from frigate.util.recording_coverage import (
coverage_spans,
known_video_codecs,
realized_timelines,
resolve_coverage,
stream_media_summary,
)
from frigate.util.time import get_dst_transitions
logger = logging.getLogger(__name__)
@@ -59,7 +71,7 @@ def get_recordings_storage_usage(request: Request):
@router.get("/recordings/summary", dependencies=[Depends(allow_any_authenticated())])
def all_recordings_summary(
async def all_recordings_summary(
request: Request,
params: MediaRecordingsSummaryQueryParams = Depends(),
allowed_cameras: list[str] = Depends(get_allowed_cameras_for_filter),
@@ -76,18 +88,23 @@ def all_recordings_summary(
else:
camera_list = allowed_cameras
time_range_query = (
Recordings.select(
fn.MIN(Recordings.start_time).alias("min_time"),
fn.MAX(Recordings.start_time).alias("max_time"),
min_time: float | None = None
max_time: float | None = None
for camera in camera_list:
cam_min = (
Recordings.select(fn.MIN(Recordings.start_time))
.where(Recordings.camera == camera)
.scalar()
)
.where(Recordings.camera << camera_list)
.dicts()
.get()
)
min_time = time_range_query.get("min_time")
max_time = time_range_query.get("max_time")
if cam_min is None:
continue
cam_max = (
Recordings.select(fn.MAX(Recordings.start_time))
.where(Recordings.camera == camera)
.scalar()
)
min_time = cam_min if min_time is None else min(min_time, cam_min)
max_time = cam_max if max_time is None else max(max_time, cam_max)
if min_time is None or max_time is None:
return JSONResponse(content={})
@@ -97,22 +114,60 @@ def all_recordings_summary(
days: dict[str, bool] = {}
for period_start, period_end, period_offset in dst_periods:
day_expr = ((Recordings.start_time + period_offset) / 86400).cast("int")
first_start = max(min_time, period_start - MAX_SEGMENT_DURATION)
first_day = int((first_start + period_offset) // 86400)
last_day = int((min(max_time, period_end) + period_offset) // 86400)
period_query = (
Recordings.select(day_expr.alias("day_idx"))
.where(
(Recordings.camera << camera_list)
& (Recordings.end_time >= period_start)
& (Recordings.start_time <= period_end)
day_idx = first_day
while day_idx <= last_day:
day_str = (dt.date(1970, 1, 1) + dt.timedelta(days=day_idx)).isoformat()
day_start = day_idx * 86400 - period_offset
day_end = day_start + 86400
if day_str in days:
day_idx += 1
continue
if day_end <= period_end:
upper = Recordings.start_time < day_end
else:
upper = Recordings.start_time <= period_end
has_recordings = (
Recordings.select(Recordings.id)
.where(
(Recordings.camera << camera_list)
& (Recordings.end_time >= period_start)
& (Recordings.start_time >= day_start)
& upper
)
.exists()
)
.distinct()
.namedtuples()
)
if has_recordings:
days[day_str] = True
day_idx += 1
continue
for g in period_query:
day_str = (dt.date(1970, 1, 1) + dt.timedelta(days=g.day_idx)).isoformat()
days[day_str] = True
# empty day
next_start: float | None = None
for camera in camera_list:
cam_next = (
Recordings.select(fn.MIN(Recordings.start_time))
.where(
Recordings.camera == camera,
Recordings.start_time >= day_end,
Recordings.start_time <= period_end,
)
.scalar()
)
if cam_next is not None and (
next_start is None or cam_next < next_start
):
next_start = cam_next
if next_start is None:
break
day_idx = max(day_idx + 1, int((next_start + period_offset) // 86400))
return JSONResponse(content=dict(sorted(days.items())))
@@ -149,23 +204,28 @@ async def recordings_summary(camera_name: str, timezone: str = "utc"):
period_hour_modifier = f"{hours_offset} hour"
period_minute_modifier = f"{minutes_offset} minute"
hour_expression = fn.strftime(
"%Y-%m-%d %H",
fn.datetime(
Recordings.start_time,
"unixepoch",
period_hour_modifier,
period_minute_modifier,
),
)
# sub rows duplicate the camera's motion/object stats, so
# aggregating them too would double-count
recording_groups = (
Recordings.select(
fn.strftime(
"%Y-%m-%d %H",
fn.datetime(
Recordings.start_time,
"unixepoch",
period_hour_modifier,
period_minute_modifier,
),
).alias("hour"),
hour_expression.alias("hour"),
fn.SUM(Recordings.duration).alias("duration"),
fn.SUM(Recordings.motion).alias("motion"),
fn.SUM(Recordings.objects).alias("objects"),
)
.where(
(Recordings.camera == camera_name)
& (Recordings.stream_type == STREAM_TYPE_MAIN)
& (Recordings.end_time >= period_start)
& (Recordings.start_time <= period_end)
)
@@ -174,6 +234,23 @@ async def recordings_summary(camera_name: str, timezone: str = "utc"):
.namedtuples()
)
# sub recordings can outlive main, so hours covered only by sub
# rows are reported too, flagged as sub_only
sub_groups = (
Recordings.select(
hour_expression.alias("hour"),
fn.SUM(Recordings.duration).alias("duration"),
)
.where(
(Recordings.camera == camera_name)
& (Recordings.stream_type == STREAM_TYPE_SUB)
& (Recordings.end_time >= period_start)
& (Recordings.start_time <= period_end)
)
.group_by((Recordings.start_time + period_offset).cast("int") / 3600)
.namedtuples()
)
event_groups = (
Event.select(
fn.strftime(
@@ -197,17 +274,43 @@ async def recordings_summary(camera_name: str, timezone: str = "utc"):
event_map = {g.hour: g.count for g in event_groups}
for recording_group in recording_groups:
parts = recording_group.hour.split()
hour_stats = [
(
g.hour,
{
"motion": g.motion,
"objects": g.objects,
"duration": round(g.duration),
},
)
for g in recording_groups
]
main_hours = {group_hour for group_hour, _ in hour_stats}
hour_stats.extend(
(
g.hour,
{
"motion": 0,
"objects": 0,
"duration": round(g.duration),
"sub_only": True,
},
)
for g in sub_groups
if g.hour not in main_hours
)
# restore the most-recent-first ordering after merging in sub hours
hour_stats.sort(key=lambda entry: entry[0], reverse=True)
for group_hour, stats in hour_stats:
parts = group_hour.split()
hour = parts[1]
day = parts[0]
events_count = event_map.get(recording_group.hour, 0)
events_count = event_map.get(group_hour, 0)
hour_data = {
"hour": hour,
"events": events_count,
"motion": recording_group.motion,
"objects": recording_group.objects,
"duration": round(recording_group.duration),
**stats,
}
if day in days:
# merge counts if already present (edge-case at DST boundary)
@@ -223,6 +326,35 @@ async def recordings_summary(camera_name: str, timezone: str = "utc"):
return JSONResponse(content=list(days.values()))
@router.get(
"/{camera_name}/recordings/coverage",
dependencies=[Depends(require_camera_access)],
)
async def recordings_coverage(
camera_name: str, after: float, before: float, timelines: bool = False
):
"""Returns merged recording coverage spans plus codec compatibility.
codecs_compatible is false only when more than one known video codec
appears across the range's rows, the case where the merged vod route
degrades to a single-stream manifest.
"""
intervals = resolve_coverage(camera_name, after, before)
content = {
"spans": coverage_spans(intervals),
"codecs_compatible": len(known_video_codecs(intervals)) <= 1,
"streams": stream_media_summary(intervals),
}
# pure computation (shared plan_clip, record-time keyframe index), but
# opt-in for payload hygiene: day-level requests need only the spans
if timelines:
content["timelines"] = realized_timelines(intervals)
return JSONResponse(content=content)
@router.get("/{camera_name}/recordings", dependencies=[Depends(require_camera_access)])
async def recordings(
camera_name: str,
@@ -243,6 +375,8 @@ async def recordings(
)
.where(
Recordings.camera == camera_name,
Recordings.stream_type == STREAM_TYPE_MAIN,
Recordings.start_time >= after - MAX_SEGMENT_DURATION,
Recordings.end_time >= after,
Recordings.start_time <= before,
)
@@ -282,22 +416,22 @@ async def no_recordings(
)
scale = params.scale
clauses = [
(Recordings.end_time >= after) & (Recordings.start_time <= before),
(Recordings.camera << camera_list),
]
recordings: list[tuple[float, float]] = []
for camera in camera_list:
recordings.extend(
Recordings.select(Recordings.start_time, Recordings.end_time)
.where(
Recordings.camera == camera,
Recordings.start_time >= after - MAX_SEGMENT_DURATION,
Recordings.end_time >= after,
Recordings.start_time <= before,
)
.tuples()
.iterator()
)
# Get recording start times
data: list[Recordings] = (
Recordings.select(Recordings.start_time, Recordings.end_time)
.where(reduce(operator.and_, clauses))
.order_by(Recordings.start_time.asc())
.dicts()
.iterator()
)
# Convert recordings to list of (start, end) tuples, ordered by start_time
recordings = [(r["start_time"], r["end_time"]) for r in data]
# the merge pass below expects a single start-ordered timeline
recordings.sort()
# Merge overlapping/adjacent recordings into covered intervals. The query
# orders by start_time, so a single pass merges them
+11 -1
View File
@@ -17,6 +17,7 @@ from frigate.api.auth import (
get_allowed_cameras_for_filter,
get_current_user,
require_camera_access,
require_full_camera_access,
require_role,
)
from frigate.api.defs.query.review_query_parameters import (
@@ -32,6 +33,7 @@ from frigate.api.defs.response.review_response import (
ReviewSummaryResponse,
)
from frigate.api.defs.tags import Tags
from frigate.const import STREAM_TYPE_MAIN
from frigate.embeddings import EmbeddingsContext
from frigate.models import Recordings, ReviewSegment, UserReviewStatus
from frigate.review.types import SeverityEnum
@@ -597,6 +599,8 @@ def motion_activity(
clauses = [(Recordings.start_time > after) & (Recordings.end_time < before)]
clauses.append(Recordings.motion > 0)
# sub rows duplicate the camera's motion stats, so only count main rows
clauses.append(Recordings.stream_type == STREAM_TYPE_MAIN)
if cameras != "all":
requested = set(cameras.split(","))
@@ -709,6 +713,7 @@ async def get_review(request: Request, review_id: str):
dependencies=[Depends(allow_any_authenticated())],
)
async def set_not_reviewed(
request: Request,
review_id: str,
current_user: dict = Depends(get_current_user),
):
@@ -727,6 +732,8 @@ async def set_not_reviewed(
status_code=404,
)
await require_camera_access(review.camera, request=request)
try:
user_review = UserReviewStatus.get(
UserReviewStatus.user_id == user_id,
@@ -743,9 +750,12 @@ async def set_not_reviewed(
)
# Intentionally not camera scoped, as the summary correlates each flagged event
# with overlapping activity on other cameras. Restricted to callers who can
# already see every camera, so the unscoped query discloses nothing.
@router.post(
"/review/summarize/start/{start_ts}/end/{end_ts}",
dependencies=[Depends(require_role(["admin"]))],
dependencies=[Depends(require_full_camera_access)],
description="Use GenAI to summarize review items over a period of time.",
)
def generate_review_summary(request: Request, start_ts: float, end_ts: float):
+40 -22
View File
@@ -49,6 +49,8 @@ from frigate.debug_replay import (
DebugReplayManager,
cleanup_replay_cameras,
)
from frigate.detectors.detector_config import SceneEnum
from frigate.detectors.device import build_detector_config, runner_names
from frigate.embeddings import EmbeddingProcess, EmbeddingsContext
from frigate.events.audio import AudioProcessor
from frigate.events.cleanup import EventCleanup
@@ -69,6 +71,7 @@ from frigate.models import (
User,
)
from frigate.object_detection.base import ObjectDetectProcess
from frigate.object_detection.util import detection_frame_size
from frigate.output.output import OutputProcess
from frigate.ptz.autotrack import PtzAutoTrackerThread
from frigate.ptz.onvif import OnvifController
@@ -98,7 +101,9 @@ class FrigateApp:
self.metrics_manager = manager
self.audio_process: mp.Process | None = None
self.stop_event = stop_event
self.detection_queue: Queue = mp.Queue()
self.detection_queues: dict[SceneEnum, Queue] = {
model.scene: mp.Queue() for model in config.models
}
self.detectors: dict[str, ObjectDetectProcess] = {}
self.detection_shms: list[mp.shared_memory.SharedMemory] = []
self.log_queue: Queue = mp.Queue()
@@ -335,6 +340,7 @@ class FrigateApp:
self.ptz_metrics,
comms,
)
self.dispatcher.start_communicators()
def init_profile_manager(self) -> None:
self.profile_manager = ProfileManager(
@@ -343,20 +349,19 @@ class FrigateApp:
self.dispatcher.profile_manager = self.profile_manager
def start_detectors(self) -> None:
model_cameras: dict[SceneEnum, list[str]] = {
model.scene: [] for model in self.config.models
}
for name in self.config.cameras.keys():
model = self.config.model_for_camera(name)
model_cameras[model.scene].append(name)
try:
largest_frame = max(
[
det.model.height * det.model.width * 3
if det.model is not None
else 320
for det in self.config.detectors.values()
]
)
shm_in = UntrackedSharedMemory(
name=name,
create=True,
size=largest_frame,
size=detection_frame_size(model),
)
except FileExistsError:
shm_in = UntrackedSharedMemory(name=name)
@@ -371,15 +376,26 @@ class FrigateApp:
self.detection_shms.append(shm_in)
self.detection_shms.append(shm_out)
for name, detector_config in self.config.detectors.items():
self.detectors[name] = ObjectDetectProcess(
name,
self.detection_queue,
list(self.config.cameras.keys()),
self.config,
detector_config,
self.stop_event,
)
# a device may be listed more than once to run additional inference
# processes on it, so names are only unique once de-duplicated
all_devices = [
device
for model in self.config.models
for device in self.config.devices_for_model(model)
]
names = iter(runner_names(all_devices))
for model in self.config.models:
for device in self.config.devices_for_model(model):
name = next(names)
self.detectors[name] = ObjectDetectProcess(
name,
self.detection_queues[model.scene],
model_cameras[model.scene],
self.config,
build_detector_config(device, model),
self.stop_event,
)
def start_ptz_autotracker(self) -> None:
self.ptz_autotracker_thread = PtzAutoTrackerThread(
@@ -410,7 +426,7 @@ class FrigateApp:
def start_camera_processor(self) -> None:
self.camera_maintainer = CameraMaintainer(
self.config,
self.detection_queue,
self.detection_queues,
self.detected_frames_queue,
self.camera_metrics,
self.ptz_metrics,
@@ -674,8 +690,10 @@ class FrigateApp:
for detector in self.detectors.values():
detector.stop()
empty_and_close_queue(self.detection_queue)
logger.info("Detection queue closed")
for detection_queue in self.detection_queues.values():
empty_and_close_queue(detection_queue)
logger.info("Detection queues closed")
self.detected_frames_processor.join()
empty_and_close_queue(self.detected_frames_queue)
+2 -1
View File
@@ -18,6 +18,7 @@ from frigate.config.camera.updater import (
CameraConfigUpdateEnum,
CameraConfigUpdateSubscriber,
)
from frigate.detectors.detector_config import NON_LOGO_ATTRIBUTES
logger = logging.getLogger(__name__)
@@ -178,7 +179,7 @@ class CameraActivityManager:
return
for label in camera_config.objects.track:
if label in self.config.model.non_logo_attributes:
if label in NON_LOGO_ATTRIBUTES:
continue
new_count = all_objects[label]
+12 -16
View File
@@ -15,7 +15,9 @@ from frigate.config.camera.updater import (
CameraConfigUpdateSubscriber,
)
from frigate.const import REPLAY_CAMERA_PREFIX
from frigate.detectors.detector_config import SceneEnum
from frigate.models import Regions
from frigate.object_detection.util import detection_frame_size
from frigate.util.builtin import empty_and_close_queue
from frigate.util.image import SharedMemoryFrameManager, UntrackedSharedMemory
from frigate.util.object import get_camera_regions_grid
@@ -29,7 +31,7 @@ class CameraMaintainer(threading.Thread):
def __init__(
self,
config: FrigateConfig,
detection_queue: Queue,
detection_queues: dict[SceneEnum, Queue],
detected_frames_queue: Queue,
camera_metrics: DictProxy,
ptz_metrics: dict[str, PTZMetrics],
@@ -38,7 +40,7 @@ class CameraMaintainer(threading.Thread):
):
super().__init__(name="camera_processor")
self.config = config
self.detection_queue = detection_queue
self.detection_queues = detection_queues
self.detected_frames_queue = detected_frames_queue
self.stop_event = stop_event
self.camera_metrics = camera_metrics
@@ -79,10 +81,11 @@ class CameraMaintainer(threading.Thread):
# create or update region grids for each camera
for camera in self.config.cameras.values():
assert camera.name is not None
model = self.config.model_for_camera(camera.name)
self.region_grids[camera.name] = get_camera_regions_grid(
camera.name,
camera.detect,
max(self.config.model.width, self.config.model.height),
max(model.width, model.height),
)
def __calculate_shm_frame_count(self) -> int:
@@ -114,6 +117,7 @@ class CameraMaintainer(threading.Thread):
return
camera_stop_event = self.__ensure_camera_stop_event(name)
model = self.config.model_for_camera(name)
if runtime:
self.camera_metrics[name] = CameraMetrics(self.metrics_manager)
@@ -123,32 +127,24 @@ class CameraMaintainer(threading.Thread):
self.region_grids[name] = get_camera_regions_grid(
name,
config.detect,
max(self.config.model.width, self.config.model.height),
max(model.width, model.height),
)
try:
largest_frame = max(
[
det.model.height * det.model.width * 3
if det.model is not None
else 320
for det in self.config.detectors.values()
]
)
UntrackedSharedMemory(name=f"out-{name}", create=True, size=20 * 6 * 4)
UntrackedSharedMemory(
name=name,
create=True,
size=largest_frame,
size=detection_frame_size(model),
)
except FileExistsError:
pass
camera_process = CameraTracker(
config,
self.config.model,
self.config.model.merged_labelmap,
self.detection_queue,
model,
model.merged_labelmap,
self.detection_queues[model.scene],
self.detected_frames_queue,
self.camera_metrics[name],
self.ptz_metrics[name],
+6 -11
View File
@@ -40,6 +40,7 @@ class CameraState:
self.name = name
self.config = config
self.camera_config = config.cameras[name]
self.model = config.model_for_camera(name)
self.frame_manager = frame_manager
self.best_objects: dict[str, TrackedObject] = {}
self.tracked_objects: dict[str, TrackedObject] = {}
@@ -101,9 +102,7 @@ class CameraState:
thickness = 1
else:
thickness = 2
color = self.config.model.colormap.get(
obj["label"], (255, 255, 255)
)
color = self.model.colormap.get(obj["label"], (255, 255, 255))
else:
thickness = 1
color = (255, 0, 0)
@@ -125,9 +124,7 @@ class CameraState:
and obj["frame_time"] == frame_time
):
thickness = 5
color = self.config.model.colormap.get(
obj["label"], (255, 255, 255)
)
color = self.model.colormap.get(obj["label"], (255, 255, 255))
# debug autotracking zooming - show the zoom factor box
if (
@@ -261,9 +258,7 @@ class CameraState:
if draw_options.get("paths"):
for obj in tracked_objects.values():
if obj["frame_time"] == frame_time and obj["path_data"]:
color = self.config.model.colormap.get(
obj["label"], (255, 255, 255)
)
color = self.model.colormap.get(obj["label"], (255, 255, 255))
path_points = [
(
@@ -366,7 +361,7 @@ class CameraState:
for id in new_ids:
logger.debug(f"{self.name}: New tracked object ID: {id}")
new_obj = tracked_objects[id] = TrackedObject(
self.config.model,
self.model,
self.camera_config,
self.config.ui,
self.frame_cache,
@@ -510,7 +505,7 @@ class CameraState:
sub_label = None
if obj.obj_data.get("sub_label"):
if obj.obj_data["sub_label"][0] in self.config.model.all_attributes:
if obj.obj_data["sub_label"][0] in self.model.all_attributes:
label = obj.obj_data["sub_label"][0]
else:
label = f"{object_type}-verified"
+17 -1
View File
@@ -1,11 +1,27 @@
from abc import ABC, abstractmethod
from collections.abc import Callable
from typing import Any
from typing import TYPE_CHECKING, Any
if TYPE_CHECKING:
from frigate.comms.dispatcher import Dispatcher
class Communicator(ABC):
"""pub/sub model via specific protocol."""
def attach_dispatcher(self, dispatcher: "Dispatcher") -> None:
"""Receive the owning dispatcher.
Transports that need more than the receiver callback (the command topic
surface, the snapshot API) take it here rather than reaching through the
bound receiver.
"""
return None
def start(self) -> None:
"""Start background I/O after receiver wiring is complete."""
return None
@abstractmethod
def publish(self, topic: str, payload: Any, retain: bool = False) -> None:
"""Send data via specific protocol."""
+132 -77
View File
@@ -11,7 +11,11 @@ from frigate.camera.activity_manager import AudioActivityManager, CameraActivity
from frigate.comms.base_communicator import Communicator
from frigate.comms.runtime_state import RuntimeStatePersistence
from frigate.comms.webpush import WebPushClient
from frigate.config import BirdseyeModeEnum, FrigateConfig
from frigate.config import (
FrigateConfig,
birdseye_modes_from_mqtt_payload,
birdseye_modes_to_mqtt_payload,
)
from frigate.config.camera.updater import (
CameraConfigUpdateEnum,
CameraConfigUpdatePublisher,
@@ -45,6 +49,11 @@ from frigate.util.services import restart_frigate
logger = logging.getLogger(__name__)
# <camera>/<command>/<sub_command>/set, one segment longer than the rest
SUB_COMMAND_TOPICS = frozenset({"motion_mask", "object_mask", "zone"})
BARE_COMMAND_TOPICS = frozenset({"onConnect", "restart"})
class Dispatcher:
"""Handle communication between Frigate and communicators."""
@@ -84,7 +93,7 @@ class Dispatcher:
"recordings": self._on_recordings_command,
"snapshots": self._on_snapshots_command,
"birdseye": self._on_birdseye_command,
"birdseye_mode": self._on_birdseye_mode_command,
"birdseye_modes": self._on_birdseye_modes_command,
"review_alerts": self._on_alerts_command,
"review_detections": self._on_detections_command,
"object_descriptions": self._on_object_description_command,
@@ -99,12 +108,114 @@ class Dispatcher:
}
self.profile_manager: ProfileManager | None = None
for comm in self.comms:
comm.subscribe(self._receive)
self.web_push_client = next(
(comm for comm in communicators if isinstance(comm, WebPushClient)), None
)
for comm in self.comms:
comm.subscribe(self._receive)
comm.attach_dispatcher(self)
def start_communicators(self) -> None:
"""Start communicators after dispatcher wiring is fully initialized."""
for comm in self.comms:
comm.start()
def is_command_topic(self, topic: str) -> bool:
"""Whether a prefix-stripped topic maps to a command handler.
Transports that fan a whole topic tree in must filter on this:
_receive() republishes anything it does not recognize, so forwarding
unfiltered would echo Frigate's own publishes back.
"""
parts = topic.split("/")
if topic in BARE_COMMAND_TOPICS:
return True
if len(parts) == 2 and parts[1] == "ptz":
return True
if len(parts) == 2 and parts[1] == "set":
return parts[0] in self._global_settings_handlers
if len(parts) == 3 and parts[2] == "set":
return (
parts[1] in self._camera_settings_handlers
and parts[1] not in SUB_COMMAND_TOPICS
)
if len(parts) == 3 and parts[2] == "suspend":
return parts[1] == "notifications"
if len(parts) == 4 and parts[3] == "set":
return parts[1] in SUB_COMMAND_TOPICS
return False
def _build_camera_activity_snapshot(self) -> tuple[dict[str, Any], dict[str, Any]]:
"""Build the current runtime activity snapshot for reconnect consumers."""
camera_status = {
camera: status
for camera, status in self.camera_activity.last_camera_activity.copy().items()
if camera in self.config.cameras
}
audio_detections = self.audio_activity.current_audio_detections.copy()
cameras_with_status = camera_status.keys()
for camera in self.config.cameras.keys():
if camera not in cameras_with_status:
camera_status[camera] = {}
camera_status[camera]["config"] = {
"detect": self.config.cameras[camera].detect.enabled,
"enabled": self.config.cameras[camera].enabled,
"snapshots": self.config.cameras[camera].snapshots.enabled,
"record": self.config.cameras[camera].record.enabled,
"audio": self.config.cameras[camera].audio.enabled,
"audio_transcription": self.config.cameras[
camera
].audio_transcription.live_enabled,
"notifications": self.config.cameras[camera].notifications.enabled,
"notifications_suspended": int(
self.web_push_client.suspended_cameras.get(camera, 0)
)
if self.web_push_client
and camera in self.web_push_client.suspended_cameras
else 0,
"autotracking": self.config.cameras[camera].onvif.autotracking.enabled,
"alerts": self.config.cameras[camera].review.alerts.enabled,
"detections": self.config.cameras[camera].review.detections.enabled,
"object_descriptions": self.config.cameras[
camera
].objects.genai.enabled,
"review_descriptions": self.config.cameras[camera].review.genai.enabled,
}
return camera_status, audio_detections
def publish_runtime_snapshot(
self,
publisher: Callable[[str, Any, bool], None] | None = None,
) -> None:
"""Publish the runtime snapshot for newly connected listeners."""
publish = publisher or self.publish
camera_status, audio_detections = self._build_camera_activity_snapshot()
publish("camera_activity", json.dumps(camera_status), False)
publish("model_state", json.dumps(self.model_state.copy()), False)
publish(
"embeddings_reindex_progress",
json.dumps(self.embeddings_reindex.copy()),
False,
)
publish("birdseye_layout", json.dumps(self.birdseye_layout.copy()), False)
publish("audio_detections", json.dumps(audio_detections), False)
publish(
"profile/state",
self.config.active_profile or "none",
True,
)
if self.web_push_client is not None:
self.web_push_client.set_suspension_broadcaster(self.publish)
@@ -123,17 +234,11 @@ class Dispatcher:
try:
if command_type == "set":
# Commands that require a sub-command (mask/zone name)
sub_command_required = {
"motion_mask",
"object_mask",
"zone",
}
if sub_command:
self._camera_settings_handlers[command](
camera_name, sub_command, payload
)
elif command in sub_command_required:
elif command in SUB_COMMAND_TOPICS:
logger.error(
"Command %s requires a sub-command (mask/zone name)",
command,
@@ -156,10 +261,11 @@ class Dispatcher:
if camera not in self.config.cameras:
return None
model = self.config.model_for_camera(camera)
grid = get_camera_regions_grid(
camera,
self.config.cameras[camera].detect,
max(self.config.model.width, self.config.model.height),
max(model.width, model.height),
)
return grid
@@ -267,67 +373,11 @@ class Dispatcher:
def handle_birdseye_layout() -> None:
self.publish("birdseye_layout", json.dumps(self.birdseye_layout.copy()))
def handle_on_connect() -> None:
camera_status = {
camera: status
for camera, status in self.camera_activity.last_camera_activity.copy().items()
if camera in self.config.cameras
}
audio_detections = self.audio_activity.current_audio_detections.copy()
cameras_with_status = camera_status.keys()
for camera in self.config.cameras.keys():
if camera not in cameras_with_status:
camera_status[camera] = {}
camera_status[camera]["config"] = {
"detect": self.config.cameras[camera].detect.enabled,
"enabled": self.config.cameras[camera].enabled,
"snapshots": self.config.cameras[camera].snapshots.enabled,
"record": self.config.cameras[camera].record.enabled,
"audio": self.config.cameras[camera].audio.enabled,
"audio_transcription": self.config.cameras[
camera
].audio_transcription.live_enabled,
"notifications": self.config.cameras[camera].notifications.enabled,
"notifications_suspended": int(
self.web_push_client.suspended_cameras.get(camera, 0)
)
if self.web_push_client
and camera in self.web_push_client.suspended_cameras
else 0,
"autotracking": self.config.cameras[
camera
].onvif.autotracking.enabled,
"alerts": self.config.cameras[camera].review.alerts.enabled,
"detections": self.config.cameras[camera].review.detections.enabled,
"object_descriptions": self.config.cameras[
camera
].objects.genai.enabled,
"review_descriptions": self.config.cameras[
camera
].review.genai.enabled,
}
self.publish("camera_activity", json.dumps(camera_status))
self.publish("model_state", json.dumps(self.model_state.copy()))
self.publish(
"embeddings_reindex_progress",
json.dumps(self.embeddings_reindex.copy()),
)
self.publish("birdseye_layout", json.dumps(self.birdseye_layout.copy()))
self.publish("audio_detections", json.dumps(audio_detections))
self.publish(
"profile/state",
self.config.active_profile or "none",
retain=True,
)
def handle_notification_test() -> None:
self.publish("notification_test", "Test notification")
# Dictionary mapping topic to handlers
topic_handlers = {
topic_handlers: dict[str, Callable[[], Any]] = {
INSERT_MANY_RECORDINGS: handle_insert_many_recordings,
REQUEST_REGION_GRID: handle_request_region_grid,
INSERT_PREVIEW: handle_insert_preview,
@@ -350,7 +400,7 @@ class Dispatcher:
"jobState": handle_job_state,
"audioTranscriptionState": handle_audio_transcription_state,
"birdseyeLayout": handle_birdseye_layout,
"onConnect": handle_on_connect,
"onConnect": self.publish_runtime_snapshot,
}
if topic.endswith("set") or topic.endswith("ptz") or topic.endswith("suspend"):
@@ -879,11 +929,12 @@ class Dispatcher:
)
self.publish(f"{camera_name}/birdseye/state", payload, retain=True)
def _on_birdseye_mode_command(self, camera_name: str, payload: str) -> None:
def _on_birdseye_modes_command(self, camera_name: str, payload: str) -> None:
"""Callback for birdseye mode topic."""
if payload not in ["CONTINUOUS", "MOTION", "OBJECTS"]:
logger.info(f"Invalid birdseye_mode command: {payload}")
modes = birdseye_modes_from_mqtt_payload(payload)
if modes is None:
logger.info("Invalid birdseye_modes command: %s", payload)
return
birdseye_settings = self.config.cameras[camera_name].birdseye
@@ -892,16 +943,20 @@ class Dispatcher:
logger.info(f"Birdseye mode not enabled for {camera_name}")
return
birdseye_settings.mode = BirdseyeModeEnum(payload.lower())
birdseye_settings.modes = modes
logger.info(
f"Setting birdseye mode for {camera_name} to {birdseye_settings.mode}"
f"Setting birdseye mode for {camera_name} to {birdseye_settings.modes}"
)
self.config_updater.publish_update(
CameraConfigUpdateTopic(CameraConfigUpdateEnum.birdseye, camera_name),
birdseye_settings,
)
self.publish(f"{camera_name}/birdseye_mode/state", payload, retain=True)
self.publish(
f"{camera_name}/birdseye_modes/state",
birdseye_modes_to_mqtt_payload(modes),
retain=True,
)
def _on_camera_notification_command(self, camera_name: str, payload: str) -> None:
"""Callback for camera level notifications topic."""
+7 -1
View File
@@ -18,10 +18,13 @@ SOCKET_REP_REQ = "ipc:///tmp/cache/comms"
class InterProcessCommunicator(Communicator):
def __init__(self) -> None:
# bound eagerly so subprocesses starting before start_communicators()
# can still connect; their requests queue in zmq until the reader runs
self.context = zmq.Context()
self.socket = self.context.socket(zmq.REP)
self.socket.bind(SOCKET_REP_REQ)
self.stop_event: MpEvent = mp.Event()
self.reader_thread: threading.Thread | None = None
def publish(self, topic: str, payload: Any, retain: bool = False) -> None:
"""There is no communication back to the processes."""
@@ -29,6 +32,8 @@ class InterProcessCommunicator(Communicator):
def subscribe(self, receiver: Callable) -> None:
self._dispatcher = receiver
def start(self) -> None:
self.reader_thread = threading.Thread(target=self.read)
self.reader_thread.start()
@@ -61,7 +66,8 @@ class InterProcessCommunicator(Communicator):
def stop(self) -> None:
self.stop_event.set()
self.reader_thread.join()
if self.reader_thread is not None:
self.reader_thread.join()
self.socket.close(linger=0)
self.context.destroy(linger=0)
+671 -170
View File
@@ -1,16 +1,38 @@
from __future__ import annotations
import logging
import queue
import threading
import time
from collections.abc import Callable
from typing import Any
from dataclasses import dataclass
from typing import TYPE_CHECKING, Any
import paho.mqtt.client as mqtt
from paho.mqtt.enums import CallbackAPIVersion
from frigate.comms.base_communicator import Communicator
from frigate.config import FrigateConfig
from frigate.config import FrigateConfig, birdseye_modes_to_mqtt_payload
if TYPE_CHECKING:
from frigate.comms.dispatcher import Dispatcher
logger = logging.getLogger(__name__)
MQTT_LOOP_TIMEOUT = 1.0
MQTT_RECONNECT_INTERVAL = 10.0
MQTT_SHUTDOWN_FLUSH_TIMEOUT = 5.0
MQTT_ON_CONNECT_RATE_LIMIT = 1.0
MQTT_PUBLISH_WAIT_INTERVAL = 0.1
@dataclass(slots=True)
class QueuedPublish:
topic: str
payload: Any
retain: bool
done: threading.Event | None = None
class MqttClient(Communicator):
"""Frigate wrapper for mqtt client."""
@@ -19,28 +41,80 @@ class MqttClient(Communicator):
self.config = config
self.mqtt_config = config.mqtt
self.connected = False
self.client: mqtt.Client | None = None
self._dispatcher: Callable[[str, Any], Any] | None = None
self._command_router: Dispatcher | None = None
self._worker: threading.Thread | None = None
self._stop_event = threading.Event()
self._publish_queue: queue.Queue[QueuedPublish] = queue.Queue()
self._callback_queue: queue.Queue[tuple[Any, ...]] = queue.Queue()
self._retained_lock = threading.Lock()
self._pending_retained: dict[str, tuple[Any, bool]] = {}
self._inflight_retained: dict[int, tuple[str, Any]] = {}
self._subscription_mid: int | None = None
self._subscription_ready = False
self._next_connect_time = 0.0
self._last_on_connect_dispatch = 0.0
def subscribe(self, receiver: Callable) -> None:
"""Wrapper for allowing dispatcher to subscribe."""
self._dispatcher = receiver
self._start()
def attach_dispatcher(self, dispatcher: Dispatcher) -> None:
"""Take Dispatcher's command surface and snapshot API."""
self._command_router = dispatcher
def start(self) -> None:
"""Start the MQTT worker after all receiver wiring is complete."""
if self._worker and self._worker.is_alive():
return
self._stop_event.clear()
self._start_worker()
def publish(self, topic: str, payload: Any, retain: bool = False) -> None:
"""Wrapper for publishing when client is in valid state."""
full_topic = f"{self.mqtt_config.topic_prefix}/{topic}"
if not self.connected:
logger.debug(f"Unable to publish to {topic}: client is not connected")
if retain:
self._queue_retained(full_topic, payload, retain)
else:
logger.debug("Unable to publish to %s: client is not connected", topic)
return
self.client.publish(
f"{self.mqtt_config.topic_prefix}/{topic}",
payload,
qos=self.config.mqtt.qos,
retain=retain,
)
self._publish_queue.put(QueuedPublish(full_topic, payload, retain))
def stop(self) -> None:
self.publish("available", "stopped", retain=True)
self.client.disconnect()
if self._worker is None:
return
if self.connected and self._subscription_ready:
publish_done = threading.Event()
self._publish_queue.put(
QueuedPublish(
f"{self.mqtt_config.topic_prefix}/available",
"stopped",
True,
publish_done,
)
)
publish_done.wait(MQTT_SHUTDOWN_FLUSH_TIMEOUT)
self._stop_event.set()
if self.client is not None:
try:
self.client.disconnect()
except Exception:
logger.debug("MQTT disconnect raised during shutdown", exc_info=True)
if self._worker.is_alive():
self._worker.join(MQTT_SHUTDOWN_FLUSH_TIMEOUT + MQTT_LOOP_TIMEOUT)
self._cleanup_client()
self._worker = None
def _notifications_enabled_in_config(self) -> bool:
"""Whether notifications are configured globally or on any camera.
@@ -54,17 +128,17 @@ class MqttClient(Communicator):
for cam in self.config.cameras.values()
)
def _set_initial_topics(self) -> None:
"""Set initial state topics."""
def _publish_retained_state(self) -> None:
"""Publish retained MQTT state after a successful subscribe."""
for camera_name, camera in self.config.cameras.items():
self.publish(
f"{camera_name}/enabled/state",
"ON" if camera.enabled_in_config else "OFF",
"ON" if camera.enabled else "OFF",
retain=True,
)
self.publish(
f"{camera_name}/recordings/state",
"ON" if camera.record.enabled_in_config else "OFF",
"ON" if camera.record.enabled else "OFF",
retain=True,
)
self.publish(
@@ -74,7 +148,7 @@ class MqttClient(Communicator):
)
self.publish(
f"{camera_name}/audio/state",
"ON" if camera.audio.enabled_in_config else "OFF",
"ON" if camera.audio.enabled else "OFF",
retain=True,
)
self.publish(
@@ -89,7 +163,7 @@ class MqttClient(Communicator):
)
self.publish(
f"{camera_name}/motion/state",
"ON",
"ON" if camera.motion.enabled else "OFF",
retain=True,
)
self.publish(
@@ -99,7 +173,7 @@ class MqttClient(Communicator):
)
self.publish(
f"{camera_name}/ptz_autotracker/state",
"ON" if camera.onvif.autotracking.enabled_in_config else "OFF",
"ON" if camera.onvif.autotracking.enabled else "OFF",
retain=True,
)
self.publish(
@@ -123,9 +197,9 @@ class MqttClient(Communicator):
retain=True,
)
self.publish(
f"{camera_name}/birdseye_mode/state",
f"{camera_name}/birdseye_modes/state",
(
camera.birdseye.mode.value.upper()
birdseye_modes_to_mqtt_payload(camera.birdseye.modes)
if camera.birdseye.enabled
else "OFF"
),
@@ -133,22 +207,22 @@ class MqttClient(Communicator):
)
self.publish(
f"{camera_name}/review_alerts/state",
"ON" if camera.review.alerts.enabled_in_config else "OFF",
"ON" if camera.review.alerts.enabled else "OFF",
retain=True,
)
self.publish(
f"{camera_name}/review_detections/state",
"ON" if camera.review.detections.enabled_in_config else "OFF",
"ON" if camera.review.detections.enabled else "OFF",
retain=True,
)
self.publish(
f"{camera_name}/object_descriptions/state",
"ON" if camera.objects.genai.enabled_in_config else "OFF",
"ON" if camera.objects.genai.enabled else "OFF",
retain=True,
)
self.publish(
f"{camera_name}/review_descriptions/state",
"ON" if camera.review.genai.enabled_in_config else "OFF",
"ON" if camera.review.genai.enabled else "OFF",
retain=True,
)
@@ -189,13 +263,521 @@ class MqttClient(Communicator):
)
self.publish("available", "online", retain=True)
def on_mqtt_command(
self, client: mqtt.Client, userdata: Any, message: mqtt.MQTTMessage
) -> None:
self._dispatcher(
message.topic.replace(f"{self.mqtt_config.topic_prefix}/", "", 1),
message.payload.decode(),
def _create_client(self) -> mqtt.Client:
"""Build a fresh paho client for a single connect attempt."""
client = mqtt.Client(
callback_api_version=CallbackAPIVersion.VERSION2,
client_id=self.mqtt_config.client_id,
reconnect_on_failure=False,
)
client.on_connect = self._on_connect
client.on_disconnect = self._on_disconnect
client.on_message = self._on_message
client.on_subscribe = self._on_subscribe
client.on_publish = self._on_publish
client.will_set(
self.mqtt_config.topic_prefix + "/available",
payload="offline",
qos=1,
retain=True,
)
if self.mqtt_config.tls_ca_certs is not None:
if (
self.mqtt_config.tls_client_cert is not None
and self.mqtt_config.tls_client_key is not None
):
client.tls_set(
self.mqtt_config.tls_ca_certs,
self.mqtt_config.tls_client_cert,
self.mqtt_config.tls_client_key,
)
else:
client.tls_set(self.mqtt_config.tls_ca_certs)
if self.mqtt_config.tls_insecure is not None:
client.tls_insecure_set(self.mqtt_config.tls_insecure)
if self.mqtt_config.user is not None:
client.username_pw_set(
self.mqtt_config.user,
password=self.mqtt_config.password,
)
return client
def _start_worker(self) -> None:
self._worker = threading.Thread(
target=self._worker_main, name="mqtt", daemon=True
)
self._worker.start()
logger.info("MQTT worker started")
def _worker_main(self) -> None:
"""Run the worker loop.
An unexpected crash disables MQTT for this session rather than taking
Frigate down with it, so it has to announce itself: without the offline
publish, consumers keep the last retained values and see a healthy
Frigate that has simply stopped updating.
"""
try:
self._mqtt_loop_worker()
except Exception:
if not self._stop_event.is_set():
logger.exception("MQTT worker crashed, disabling MQTT for this session")
self._stop_event.set()
self._subscription_ready = False
self._publish_offline_availability()
self.connected = False
finally:
# nothing drains the queue once the loop is gone, so release any
# waiter here or stop() blocks for the full flush timeout
self._requeue_disconnected_publishes()
self._cleanup_client()
def _publish_offline_availability(self) -> None:
"""Announce that MQTT is going away after a worker crash.
_cleanup_client() disconnects cleanly, which tells the broker to
suppress the will, so the retained topic would otherwise stay "online".
"""
if self.client is None:
return
try:
message_info = self.client.publish(
f"{self.mqtt_config.topic_prefix}/available",
"offline",
qos=self.config.mqtt.qos,
retain=True,
)
# pumped here rather than through _wait_for_publish() so the drain
# that may have just crashed is not re-entered
deadline = time.monotonic() + MQTT_SHUTDOWN_FLUSH_TIMEOUT
while not message_info.is_published() and time.monotonic() < deadline:
if (
self.client.loop(timeout=MQTT_PUBLISH_WAIT_INTERVAL)
!= mqtt.MQTT_ERR_SUCCESS
):
break
except Exception:
logger.warning(
"MQTT is dormant and the broker could not be told Frigate is offline",
exc_info=True,
)
def _mqtt_loop_worker(self) -> None:
# The worker owns all socket I/O so reconnect, subscribe, and publish
# ordering stays serialized in one place.
while not self._stop_event.is_set():
if self.client is None:
wait_time = self._next_connect_time - time.monotonic()
if wait_time > 0:
self._stop_event.wait(min(wait_time, MQTT_LOOP_TIMEOUT))
continue
if not self._connect_client():
self._next_connect_time = time.monotonic() + MQTT_RECONNECT_INTERVAL
continue
assert self.client is not None
try:
result = self.client.loop(timeout=MQTT_LOOP_TIMEOUT)
except (OSError, mqtt.WebsocketConnectionError) as err:
logger.warning("MQTT loop error: %s", err)
self._schedule_reconnect()
continue
self._drain_callback_queue()
self._drain_publish_queue()
if self._stop_event.is_set():
break
if result != mqtt.MQTT_ERR_SUCCESS and self.client is not None:
logger.error("MQTT loop returned error code: %s", result)
self._schedule_reconnect()
def _connect_client(self) -> bool:
"""Create and connect a new client instance owned by the worker thread."""
try:
self.client = self._create_client()
self.client.connect(self.mqtt_config.host, self.mqtt_config.port, 60)
except Exception as err:
logger.error("Unable to connect to MQTT server: %s", err)
self._cleanup_client()
return False
return True
def _cleanup_client(self) -> None:
"""Drop session-specific state and release the current paho client."""
self.connected = False
self._subscription_ready = False
self._subscription_mid = None
self._requeue_inflight_retained()
client = self.client
self.client = None
if client is None:
return
try:
client.disconnect()
except Exception:
logger.debug("MQTT client cleanup raised disconnect error", exc_info=True)
def _schedule_reconnect(self) -> None:
"""Tear down the current session and arm the next reconnect attempt."""
if self._stop_event.is_set():
return
self.connected = False
self._subscription_ready = False
self._subscription_mid = None
self._requeue_disconnected_publishes()
self._next_connect_time = time.monotonic() + MQTT_RECONNECT_INTERVAL
logger.info("MQTT reconnect scheduled in %.1fs", MQTT_RECONNECT_INTERVAL)
self._cleanup_client()
def _requeue_inflight_retained(self) -> None:
"""Rebuffer retained publishes paho took but the broker never acked.
Dropping the client drops paho's outbound queue with it, and the session
is clean, so the broker will not resume delivery on the new one.
"""
with self._retained_lock:
# mids are insertion ordered, so collapsing by topic keeps the
# newest value when several updates to one topic were in flight
latest = {
topic: payload for topic, payload in self._inflight_retained.values()
}
self._inflight_retained.clear()
for topic, payload in latest.items():
self._queue_retained(topic, payload, True, overwrite=False)
def _buffer_undelivered(
self, queued_publish: QueuedPublish, overwrite: bool = True
) -> None:
"""Handle a publish that never reached the broker.
Releasing the waiter matters on every path: stop() blocks on it, so a
broker error would otherwise stall shutdown for the full flush timeout.
"""
if queued_publish.retain:
self._queue_retained(
queued_publish.topic,
queued_publish.payload,
queued_publish.retain,
overwrite=overwrite,
)
if queued_publish.done is not None:
queued_publish.done.set()
def _requeue_disconnected_publishes(self) -> None:
while True:
try:
queued_publish = self._publish_queue.get_nowait()
except queue.Empty:
break
self._buffer_undelivered(queued_publish)
def _drain_callback_queue(self) -> None:
# Paho callbacks only enqueue transport events; state transitions run
# here on the worker thread.
while True:
try:
event = self._callback_queue.get_nowait()
except queue.Empty:
break
event_type = event[0]
if event_type == "connect":
self._handle_connect_event(event[1])
elif event_type == "connect_failure":
self._handle_connect_failure(event[1])
elif event_type == "disconnect":
self._handle_disconnect_event(event[1])
elif event_type == "subscribed":
self._handle_subscribe_event(event[1], event[2])
elif event_type == "message":
self._handle_inbound_message(event[1], event[2])
elif event_type == "published":
self._handle_publish_event(event[1])
def _drain_publish_queue(self) -> None:
"""Publish queued work only after the session is fully subscribed.
Oldest first: the outage buffer replays before the queue, so a topic
that changed since the reconnect ends up on its newest value rather
than being reverted by the replay.
"""
if self.connected and not self._subscription_ready:
return
self._flush_pending_retained()
while True:
try:
queued_publish = self._publish_queue.get_nowait()
except queue.Empty:
break
if not self.connected:
self._buffer_undelivered(queued_publish)
continue
self._publish_direct(queued_publish)
def _flush_pending_retained(self) -> None:
"""Replay the latest retained state once the broker session is ready."""
if not self.connected or not self._subscription_ready:
return
with self._retained_lock:
pending = list(self._pending_retained.items())
self._pending_retained.clear()
for topic, (payload, retain) in pending:
self._publish_direct(QueuedPublish(topic, payload, retain))
def _publish_direct(self, queued_publish: QueuedPublish) -> None:
"""Publish a queued message from the worker thread's serialized context.
The waiter is released however this exits. The message is already off
the queue by now, so nothing else can recover it for a stop() that is
blocked waiting on it.
"""
try:
if self.client is None:
# never attempted, so anything already buffered for this topic
# was written later and has to survive
self._buffer_undelivered(queued_publish, overwrite=False)
return
try:
message_info = self.client.publish(
queued_publish.topic,
queued_publish.payload,
qos=self.config.mqtt.qos,
retain=queued_publish.retain,
)
except (OSError, mqtt.WebsocketConnectionError) as err:
logger.warning(
"MQTT publish failed for %s: %s", queued_publish.topic, err
)
# a newer buffered value for this topic wins over the failed one
self._buffer_undelivered(queued_publish, overwrite=False)
self._schedule_reconnect()
return
if message_info.rc != mqtt.MQTT_ERR_SUCCESS:
logger.error(
"Unable to publish to %s: mqtt error %s",
queued_publish.topic,
message_info.rc,
)
self._buffer_undelivered(queued_publish, overwrite=False)
self._schedule_reconnect()
return
# a successful rc only means paho accepted the message; above qos 0
# it is not durable until the broker acks, so keep a copy for replay
if queued_publish.retain and not message_info.is_published():
with self._retained_lock:
self._inflight_retained[message_info.mid] = (
queued_publish.topic,
queued_publish.payload,
)
if queued_publish.done is not None:
self._wait_for_publish(message_info)
finally:
if queued_publish.done is not None:
queued_publish.done.set()
def _handle_publish_event(self, mid: int) -> None:
"""Drop the replay copy once the broker has acknowledged the message."""
with self._retained_lock:
self._inflight_retained.pop(mid, None)
def _wait_for_publish(self, message_info: mqtt.MQTTMessageInfo) -> None:
"""Pump the loop until a shutdown-critical publish is acknowledged."""
deadline = time.monotonic() + MQTT_SHUTDOWN_FLUSH_TIMEOUT
while not message_info.is_published() and time.monotonic() < deadline:
if self.client is None:
return
try:
result = self.client.loop(timeout=MQTT_PUBLISH_WAIT_INTERVAL)
except (OSError, mqtt.WebsocketConnectionError) as err:
logger.warning("MQTT publish wait failed: %s", err)
self._schedule_reconnect()
return
self._drain_callback_queue()
if result != mqtt.MQTT_ERR_SUCCESS:
logger.error(
"MQTT loop returned error code while waiting for publish: %s",
result,
)
self._schedule_reconnect()
return
def _queue_retained(
self,
topic: str,
payload: Any,
retain: bool,
overwrite: bool = True,
) -> None:
"""Store the last retained value per topic for replay after reconnect."""
with self._retained_lock:
if overwrite or topic not in self._pending_retained:
self._pending_retained[topic] = (payload, retain)
def _handle_connect_event(self, reason_code: mqtt.ReasonCode) -> None: # type: ignore[name-defined]
"""Begin a new session by subscribing before any replay is published."""
if self.client is None:
return
self.connected = True
self._subscription_ready = False
self._subscription_mid = None
logger.debug("MQTT connected")
try:
result, mid = self.client.subscribe(
f"{self.mqtt_config.topic_prefix}/#",
qos=self.config.mqtt.qos,
)
except (OSError, mqtt.WebsocketConnectionError) as err:
logger.warning("MQTT subscribe failed: %s", err)
self._schedule_reconnect()
return
if result != mqtt.MQTT_ERR_SUCCESS:
logger.error(
"Unable to subscribe to MQTT command tree: mqtt error %s", result
)
self._schedule_reconnect()
return
self._subscription_mid = mid
def _handle_connect_failure(self, reason_code: mqtt.ReasonCode) -> None: # type: ignore[name-defined]
"""Record a failed connect attempt and transition into reconnect state."""
self.connected = False
logger.error(
"Unable to connect to MQTT server: %s", self._reason_code_name(reason_code)
)
self._schedule_reconnect()
def _handle_disconnect_event(self, reason_code: mqtt.ReasonCode) -> None: # type: ignore[name-defined]
"""Handle broker disconnects idempotently from the worker thread."""
if not self.connected:
return
self.connected = False
self._subscription_ready = False
self._subscription_mid = None
if self._stop_event.is_set():
logger.debug("MQTT disconnected")
self._cleanup_client()
return
logger.error("MQTT disconnected: %s", self._reason_code_name(reason_code))
self._schedule_reconnect()
def _handle_subscribe_event(
self,
mid: int,
reason_codes: list[mqtt.ReasonCode], # type: ignore[name-defined]
) -> None:
"""Mark the session ready after SUBACK, then replay retained/runtime state."""
if mid != self._subscription_mid:
return
if any(
getattr(reason_code, "is_failure", False) for reason_code in reason_codes
):
logger.error("MQTT subscription was rejected by the broker")
self._schedule_reconnect()
return
self._subscription_ready = True
self._subscription_mid = None
# a bug in replay should cost a snapshot, not the MQTT session
try:
self._publish_retained_state()
if self._command_router is not None:
self._command_router.publish_runtime_snapshot(self.publish)
except Exception:
logger.exception("Error replaying MQTT state after subscribe")
def _handle_inbound_message(self, topic: str, payload: str) -> None:
"""Forward supported command topics into Dispatcher semantics."""
if self._dispatcher is None:
return
if not self._is_supported_command_topic(topic):
return
if topic == "onConnect":
now = time.monotonic()
if now - self._last_on_connect_dispatch < MQTT_ON_CONNECT_RATE_LIMIT:
logger.debug("Skipping MQTT onConnect replay request due to rate limit")
return
self._last_on_connect_dispatch = now
# a raise here used to end the network thread and take MQTT down
try:
self._dispatcher(topic, payload)
except Exception:
logger.exception("Error handling MQTT command topic %s", topic)
def _is_supported_command_topic(self, topic: str) -> bool:
"""Filter the wildcard subscription down to Dispatcher's command surface.
Load-bearing rather than an optimization: the broker echoes Frigate's own
publishes back through frigate/#, and Dispatcher republishes topics it
does not recognize, so forwarding unfiltered would loop.
"""
if self._command_router is None:
return False
# mirrors the gate on the state topic in _publish_retained_state()
if topic == "notifications/set" and not self._notifications_enabled_in_config():
return False
return self._command_router.is_command_topic(topic)
def _strip_topic_prefix(self, topic: str) -> str:
return topic.replace(f"{self.mqtt_config.topic_prefix}/", "", 1)
def _is_success_reason_code(self, reason_code: mqtt.ReasonCode) -> bool: # type: ignore[name-defined]
if hasattr(reason_code, "is_failure"):
return not bool(reason_code.is_failure)
return bool(reason_code == 0)
def _reason_code_name(self, reason_code: mqtt.ReasonCode) -> str: # type: ignore[name-defined]
if hasattr(reason_code, "getName"):
return str(reason_code.getName())
return str(reason_code)
def _on_connect(
self,
@@ -205,29 +787,11 @@ class MqttClient(Communicator):
reason_code: mqtt.ReasonCode, # type: ignore[name-defined]
properties: Any,
) -> None:
"""Mqtt connection callback."""
threading.current_thread().name = "mqtt"
if reason_code != 0:
if reason_code == "Server unavailable":
logger.error(
"Unable to connect to MQTT server: MQTT Server unavailable"
)
elif reason_code == "Bad user name or password":
logger.error(
"Unable to connect to MQTT server: MQTT Bad username or password"
)
elif reason_code == "Not authorized":
logger.error("Unable to connect to MQTT server: MQTT Not authorized")
else:
logger.error(
"Unable to connect to MQTT server: Connection refused. Error code: %s",
reason_code.getName(),
)
self.connected = True
logger.debug("MQTT connected")
client.subscribe(f"{self.mqtt_config.topic_prefix}/#", qos=self.config.mqtt.qos)
self._set_initial_topics()
"""Handle broker connect notifications from paho."""
if self._is_success_reason_code(reason_code):
self._callback_queue.put(("connect", reason_code))
else:
self._callback_queue.put(("connect_failure", reason_code))
def _on_disconnect(
self,
@@ -237,126 +801,63 @@ class MqttClient(Communicator):
reason_code: mqtt.ReasonCode, # type: ignore[name-defined]
properties: Any,
) -> None:
"""Mqtt disconnection callback."""
self.connected = False
logger.error("MQTT disconnected")
"""Handle broker disconnect notifications from paho."""
self._callback_queue.put(("disconnect", reason_code))
def _start(self) -> None:
"""Start mqtt client."""
self.client = mqtt.Client(
callback_api_version=CallbackAPIVersion.VERSION2,
client_id=self.mqtt_config.client_id,
)
self.client.on_connect = self._on_connect
self.client.on_disconnect = self._on_disconnect
self.client.will_set(
self.mqtt_config.topic_prefix + "/available",
payload="offline",
qos=1,
retain=True,
)
def _on_subscribe(
self,
client: mqtt.Client,
userdata: Any,
mid: int,
reason_codes: list[mqtt.ReasonCode], # type: ignore[name-defined]
properties: Any,
) -> None:
"""Handle subscribe acknowledgements from paho."""
self._callback_queue.put(("subscribed", mid, reason_codes))
# register callbacks
callback_types = [
"enabled",
"recordings",
"snapshots",
"detect",
"audio",
"audio_transcription",
"motion",
"improve_contrast",
"ptz_autotracker",
"motion_threshold",
"motion_contour_area",
"birdseye",
"birdseye_mode",
"review_alerts",
"review_detections",
"object_descriptions",
"review_descriptions",
"notifications",
]
def _on_publish(
self,
client: mqtt.Client,
userdata: Any,
mid: int,
reason_code: mqtt.ReasonCode, # type: ignore[name-defined]
properties: Any,
) -> None:
"""Handle publish acknowledgements from paho.
for name in self.config.cameras.keys():
for callback in callback_types:
self.client.message_callback_add(
f"{self.mqtt_config.topic_prefix}/{name}/{callback}/set",
self.on_mqtt_command,
)
Only tracked retained messages need an event. At the default qos 0
nothing is tracked, so this stays off the hot publish path.
"""
with self._retained_lock:
if mid not in self._inflight_retained:
return
# notifications suspend doesn't follow the /set topic pattern
self.client.message_callback_add(
f"{self.mqtt_config.topic_prefix}/{name}/notifications/suspend",
self.on_mqtt_command,
)
self._callback_queue.put(("published", mid))
if self.config.cameras[name].onvif.host:
self.client.message_callback_add(
f"{self.mqtt_config.topic_prefix}/{name}/ptz",
self.on_mqtt_command,
)
def _on_message(
self,
client: mqtt.Client,
userdata: Any,
message: mqtt.MQTTMessage,
) -> None:
"""Queue inbound MQTT messages for processing in the worker loop."""
topic = self._strip_topic_prefix(message.topic)
for mask_name in self.config.cameras[name].motion.mask.keys():
self.client.message_callback_add(
f"{self.mqtt_config.topic_prefix}/{name}/motion_mask/{mask_name}/set",
self.on_mqtt_command,
)
for mask_name in self.config.cameras[name].objects.mask.keys():
self.client.message_callback_add(
f"{self.mqtt_config.topic_prefix}/{name}/object_mask/{mask_name}/set",
self.on_mqtt_command,
)
for zone_name in self.config.cameras[name].zones.keys():
self.client.message_callback_add(
f"{self.mqtt_config.topic_prefix}/{name}/zone/{zone_name}/set",
self.on_mqtt_command,
)
if self._notifications_enabled_in_config():
self.client.message_callback_add(
f"{self.mqtt_config.topic_prefix}/notifications/set",
self.on_mqtt_command,
)
self.client.message_callback_add(
f"{self.mqtt_config.topic_prefix}/profile/set",
self.on_mqtt_command,
)
self.client.message_callback_add(
f"{self.mqtt_config.topic_prefix}/onConnect", self.on_mqtt_command
)
self.client.message_callback_add(
f"{self.mqtt_config.topic_prefix}/restart", self.on_mqtt_command
)
if self.mqtt_config.tls_ca_certs is not None:
if (
self.mqtt_config.tls_client_cert is not None
and self.mqtt_config.tls_client_key is not None
):
self.client.tls_set(
self.mqtt_config.tls_ca_certs,
self.mqtt_config.tls_client_cert,
self.mqtt_config.tls_client_key,
)
else:
self.client.tls_set(self.mqtt_config.tls_ca_certs)
if self.mqtt_config.tls_insecure is not None:
self.client.tls_insecure_set(self.mqtt_config.tls_insecure)
if self.mqtt_config.user is not None:
self.client.username_pw_set(
self.mqtt_config.user, password=self.mqtt_config.password
)
try:
# https://stackoverflow.com/a/55390477
# with connect_async, retries are handled automatically
self.client.connect_async(self.mqtt_config.host, self.mqtt_config.port, 60)
self.client.loop_start()
except Exception as e:
logger.error(f"Unable to connect to MQTT server: {e}")
# Ignore everything outside Frigate's command surface before decoding or
# dispatching into the rest of the app.
if not self._is_supported_command_topic(topic):
return
try:
payload = message.payload.decode()
except UnicodeDecodeError:
logger.debug("Ignoring non-UTF-8 MQTT payload for topic %s", topic)
return
self._callback_queue.put(
(
"message",
topic,
payload,
)
)
+26 -16
View File
@@ -63,14 +63,8 @@ class WebPushClient(Communicator):
self.last_notification_time: float = 0
self.user_cameras: dict[str, set[str]] = {}
self.notification_queue: queue.Queue[PushNotification] = queue.Queue()
self.notification_thread = threading.Thread(
target=self._process_notifications, daemon=True
)
self.notification_thread.start()
self.suspension_thread = threading.Thread(
target=self._process_suspensions, daemon=True
)
self.suspension_thread.start()
self.notification_thread: threading.Thread | None = None
self.suspension_thread: threading.Thread | None = None
if not self.config.notifications.email:
logger.warning("Email must be provided for push notifications to be sent.")
@@ -99,6 +93,16 @@ class WebPushClient(Communicator):
"""Wrapper for allowing dispatcher to subscribe."""
pass
def start(self) -> None:
self.notification_thread = threading.Thread(
target=self._process_notifications, daemon=True
)
self.notification_thread.start()
self.suspension_thread = threading.Thread(
target=self._process_suspensions, daemon=True
)
self.suspension_thread.start()
def check_registrations(self) -> None:
# check for valid claim or create new one
now = datetime.datetime.now().timestamp()
@@ -220,7 +224,9 @@ class WebPushClient(Communicator):
if topic == "reviews":
decoded = json.loads(payload)
camera = decoded["before"]["camera"]
if not self.config.cameras[camera].notifications.enabled:
camera_config = self.config.cameras.get(camera)
if camera_config is None or not camera_config.notifications.enabled:
return
if self.is_camera_suspended(camera):
logger.debug(f"Notifications for {camera} are currently suspended.")
@@ -234,13 +240,14 @@ class WebPushClient(Communicator):
# ensure notifications are enabled and the specific trigger has
# notification action enabled
camera_config = self.config.cameras.get(camera)
if (
not self.config.cameras[camera].notifications.enabled
or name not in self.config.cameras[camera].semantic_search.triggers
camera_config is None
or not camera_config.notifications.enabled
or name not in camera_config.semantic_search.triggers
or "notification"
not in self.config.cameras[camera]
.semantic_search.triggers[name]
.actions
not in camera_config.semantic_search.triggers[name].actions
):
return
@@ -251,7 +258,9 @@ class WebPushClient(Communicator):
elif topic == "camera_monitoring":
decoded = json.loads(payload)
camera = decoded["camera"]
if not self.config.cameras[camera].notifications.enabled:
camera_config = self.config.cameras.get(camera)
if camera_config is None or not camera_config.notifications.enabled:
return
if self.is_camera_suspended(camera):
logger.debug(f"Notifications for {camera} are currently suspended.")
@@ -602,4 +611,5 @@ class WebPushClient(Communicator):
def stop(self) -> None:
logger.info("Closing notification queue")
self.notification_thread.join()
if self.notification_thread is not None:
self.notification_thread.join()
-1
View File
@@ -466,7 +466,6 @@ class WebSocketClient(Communicator):
def subscribe(self, receiver: Callable) -> None:
self._dispatcher = receiver
self.start()
def start(self) -> None:
"""Start the websocket client."""
+5
View File
@@ -41,6 +41,11 @@ class AudioConfig(FrigateBaseModel):
title="Listen types",
description="List of audio event types to detect (for example: bark, fire_alarm, speech, yell).",
)
labelmap: dict[int, str] = Field(
default_factory=dict,
title="Audio labelmap customization",
description="Overrides or remapping entries to merge into the standard audio labelmap.",
)
filters: dict[str, AudioFilterConfig] | None = Field(
None,
title="Audio filters",
+52 -16
View File
@@ -9,21 +9,57 @@ __all__ = [
"BirdseyeConfig",
"BirdseyeLayoutConfig",
"BirdseyeModeEnum",
"birdseye_modes_from_mqtt_payload",
"birdseye_modes_to_mqtt_payload",
]
# canonical MQTT payload for an empty mode list
MQTT_NO_MODES = "NONE"
class BirdseyeModeEnum(str, Enum):
objects = "objects"
motion = "motion"
continuous = "continuous"
motion = "motion"
all_objects = "all_objects"
alerts = "alerts"
detections = "detections"
@classmethod
def get_index(cls, type):
return list(cls).index(type)
@classmethod
def get(cls, index):
return list(cls)[index]
def birdseye_modes_from_mqtt_payload(payload: str) -> list[BirdseyeModeEnum] | None:
"""Parse an uppercase MQTT payload into activity modes, or None when invalid."""
raw_modes = payload.split(",")
if any(not raw_mode or raw_mode != raw_mode.upper() for raw_mode in raw_modes):
return None
if raw_modes == [MQTT_NO_MODES]:
return []
modes: list[BirdseyeModeEnum] = []
for raw_mode in raw_modes:
try:
mode = BirdseyeModeEnum(raw_mode.lower())
except ValueError:
return None
if mode in modes:
return None
modes.append(mode)
return modes
def birdseye_modes_to_mqtt_payload(modes: list[BirdseyeModeEnum]) -> str:
"""Serialize activity modes for MQTT state topics."""
payload = ",".join(mode.value.upper() for mode in BirdseyeModeEnum if mode in modes)
return payload or MQTT_NO_MODES
def default_birdseye_modes() -> list[BirdseyeModeEnum]:
"""Return the default Birdseye activity modes."""
return [BirdseyeModeEnum.all_objects]
class BirdseyeLayoutConfig(FrigateBaseModel):
@@ -47,10 +83,10 @@ class BirdseyeConfig(FrigateBaseModel):
title="Enable Birdseye",
description="Enable or disable the Birdseye view feature.",
)
mode: BirdseyeModeEnum = Field(
default=BirdseyeModeEnum.objects,
title="Tracking mode",
description="Mode for including cameras in Birdseye: 'objects', 'motion', or 'continuous'.",
modes: list[BirdseyeModeEnum] = Field(
default_factory=default_birdseye_modes,
title="Activity types",
description="Activity types that include cameras in Birdseye.",
)
restream: bool = Field(
@@ -102,10 +138,10 @@ class BirdseyeCameraConfig(BaseModel):
title="Enable Birdseye",
description="Enable or disable the Birdseye view feature.",
)
mode: BirdseyeModeEnum = Field(
default=BirdseyeModeEnum.objects,
title="Tracking mode",
description="Mode for including cameras in Birdseye: 'objects', 'motion', or 'continuous'.",
modes: list[BirdseyeModeEnum] = Field(
default_factory=default_birdseye_modes,
title="Activity types",
description="Activity types that include cameras in Birdseye.",
)
order: int = Field(
+28 -1
View File
@@ -3,7 +3,12 @@ from enum import Enum
from pydantic import Field, PrivateAttr, model_validator
from frigate.const import CACHE_DIR, CACHE_SEGMENT_FORMAT, REGEX_CAMERA_NAME
from frigate.const import (
CACHE_DIR,
CACHE_SEGMENT_FORMAT,
REGEX_CAMERA_NAME,
SUB_CACHE_TAG,
)
from frigate.ffmpeg_presets import (
parse_preset_hardware_acceleration_decode,
parse_preset_hardware_acceleration_scale,
@@ -294,6 +299,28 @@ class CameraConfig(FrigateBaseModel):
+ ffmpeg_output_args
)
if (
"record_sub" in ffmpeg_input.roles
and self.record.enabled
and self.record.sub.enabled
):
sub_output_args = self.ffmpeg.output_args.effective_record_sub
record_args = get_ffmpeg_arg_list(
parse_preset_output_record(
sub_output_args,
self.ffmpeg.apple_compatibility,
)
or sub_output_args
)
ffmpeg_output_args = (
record_args
+ [
f"{os.path.join(CACHE_DIR, self.name)}{SUB_CACHE_TAG}@{CACHE_SEGMENT_FORMAT}.mp4"
]
+ ffmpeg_output_args
)
# if there aren't any outputs enabled for this input
if len(ffmpeg_output_args) == 0:
return None
+7
View File
@@ -1,5 +1,7 @@
from pydantic import Field, model_validator
from frigate.detectors.detector_config import SceneEnum
from ..base import FrigateBaseModel
__all__ = ["DetectConfig", "StationaryConfig", "StationaryMaxFramesConfig"]
@@ -60,6 +62,11 @@ class DetectConfig(FrigateBaseModel):
title="Detect width",
description="Width (pixels) of frames used for the detect stream; leave empty to use the native stream resolution.",
)
scene: SceneEnum = Field(
default=SceneEnum.all,
title="Detect scene",
description="The environment this camera looks at, used to pick which of the configured models runs on it. Cameras left on 'all' run the model configured with a scene of 'all'.",
)
fps: int = Field(
default=5,
title="Detect FPS",
+15
View File
@@ -42,6 +42,20 @@ class FfmpegOutputArgsConfig(FrigateBaseModel):
title="Record output arguments",
description="Default output arguments for record role streams.",
)
record_sub: str | list[str] = Field(
default_factory=list,
title="Sub stream record output arguments",
description="Output arguments for record_sub role streams. The record output arguments are used when this is not set.",
)
@property
def effective_record_sub(self) -> str | list[str]:
"""Output arguments used for the record_sub role.
Falls back to the record arguments rather than to the stock preset so
that a customized record value keeps applying to both recorded streams.
"""
return self.record_sub or self.record
class FfmpegConfig(FrigateBaseModel):
@@ -99,6 +113,7 @@ class FfmpegConfig(FrigateBaseModel):
class CameraRoleEnum(str, Enum):
audio = "audio"
record = "record"
record_sub = "record_sub"
detect = "detect"
+52
View File
@@ -13,6 +13,7 @@ __all__ = [
"RecordExportConfig",
"RecordPreviewConfig",
"RecordQualityEnum",
"RecordSubConfig",
"EventsConfig",
"ReviewRetainConfig",
"RecordRetainConfig",
@@ -110,6 +111,34 @@ class RecordExportConfig(FrigateBaseModel):
)
class RecordSubConfig(FrigateBaseModel):
enabled: bool = Field(
default=False,
title="Enable sub stream recording",
description="Enable recording of a second, lower quality stream for adaptive quality playback and extended retention.",
)
continuous: RecordRetainConfig = Field(
default_factory=RecordRetainConfig,
title="Sub stream continuous retention",
description="Number of days to retain sub stream recordings regardless of tracked objects or motion.",
)
motion: RecordRetainConfig = Field(
default_factory=RecordRetainConfig,
title="Sub stream motion retention",
description="Number of days to retain sub stream recordings triggered by motion.",
)
alerts: ReviewRetainConfig = Field(
default_factory=ReviewRetainConfig,
title="Sub stream alert retention",
description="Retention settings for sub stream recordings of alerts.",
)
detections: ReviewRetainConfig = Field(
default_factory=ReviewRetainConfig,
title="Sub stream detection retention",
description="Retention settings for sub stream recordings of detections.",
)
class RecordConfig(FrigateBaseModel):
enabled: bool = Field(
default=False,
@@ -151,12 +180,35 @@ class RecordConfig(FrigateBaseModel):
title="Preview config",
description="Settings controlling the quality of recording previews shown in the UI.",
)
sub: RecordSubConfig = Field(
default_factory=RecordSubConfig,
title="Sub stream recording",
description="Settings for recording a second, lower quality stream.",
)
enabled_in_config: bool | None = Field(
default=None,
title="Original recording state",
description="Indicates whether recording was enabled in the original static configuration.",
)
@property
def effective_alert_days(self) -> float:
"""Alert retention extended to the sub stream window when sub is enabled.
Review items and tracked objects must stay visible for as long as
either stream still has recordings.
"""
if self.sub.enabled:
return max(self.alerts.retain.days, self.sub.alerts.days)
return self.alerts.retain.days
@property
def effective_detection_days(self) -> float:
"""Detection retention extended to the sub window when sub is enabled."""
if self.sub.enabled:
return max(self.detections.retain.days, self.sub.detections.days)
return self.detections.retain.days
@property
def event_pre_capture(self) -> int:
return max(
+7 -1
View File
@@ -96,6 +96,7 @@ class CameraConfigUpdateSubscriber:
return
elif update_type == CameraConfigUpdateEnum.remove:
self.config.cameras.pop(camera, None)
self.config.drop_camera_model(camera)
self.camera_configs.pop(camera, None)
return
@@ -129,8 +130,13 @@ class CameraConfigUpdateSubscriber:
config.objects = updated_config
elif update_type == CameraConfigUpdateEnum.record:
old_enabled_in_config = config.record.enabled_in_config
old_sub_enabled = config.record.sub.enabled
config.record = updated_config
if old_enabled_in_config != updated_config.enabled_in_config:
# the record and record_sub ffmpeg outputs are gated on these
if (
old_enabled_in_config != updated_config.enabled_in_config
or old_sub_enabled != updated_config.sub.enabled
):
config.recreate_ffmpeg_cmds()
elif update_type == CameraConfigUpdateEnum.review:
config.review = updated_config
+285 -68
View File
@@ -11,7 +11,6 @@ from pydantic import (
BaseModel,
ConfigDict,
Field,
TypeAdapter,
ValidationInfo,
field_validator,
model_validator,
@@ -19,8 +18,9 @@ from pydantic import (
from ruamel.yaml import YAML
from frigate.const import REGEX_JSON
from frigate.detectors import DetectorConfig, ModelConfig
from frigate.detectors.detector_config import BaseDetectorConfig
from frigate.detectors import ModelConfig
from frigate.detectors.detector_config import SceneEnum
from frigate.detectors.device import DeviceParseError, DeviceSpec, parse_device
from frigate.plus import PlusApi
from frigate.util.builtin import (
deep_merge,
@@ -63,7 +63,7 @@ from .classification import (
SemanticSearchModelEnum,
)
from .database import DatabaseConfig
from .env import EnvVars
from .env import EnvVars, reload_sources
from .logger import LoggerConfig
from .mqtt import MqttConfig
from .network import NetworkingConfig
@@ -79,9 +79,14 @@ logger = logging.getLogger(__name__)
yaml = YAML()
# Pydantic field default applied when an existing config omits `detectors:`.
# Pydantic field default applied when an existing config omits `models:`.
# Kept as cpu tflite for backwards compatibility with 0.17 configs.
DEFAULT_DETECTORS = {"cpu": {"type": "cpu"}}
DEFAULT_MODELS = [{"devices": ["cpu"]}]
def _default_models() -> list[ModelConfig]:
return [ModelConfig.model_validate(model) for model in DEFAULT_MODELS]
# Used by the openvino branch below and rendered into the new-config YAML
# template so first-time setups default to openvino on CPU.
@@ -93,7 +98,7 @@ DEFAULT_MODEL = {
"path": "/openvino-model/ssdlite_mobilenet_v2.xml",
"labelmap_path": "/openvino-model/coco_91cl_bkgr.txt",
}
NEW_CONFIG_DETECTORS = {"ov": {"type": "openvino", "device": "CPU"}}
NEW_CONFIG_MODELS = [{"devices": ["openvino:CPU"], **DEFAULT_MODEL}]
DEFAULT_DETECT_DIMENSIONS = {"width": 1280, "height": 720}
@@ -109,7 +114,7 @@ DEFAULT_CONFIG = f"""
mqtt:
enabled: False
{_render_default_yaml({"detectors": NEW_CONFIG_DETECTORS, "model": DEFAULT_MODEL})}
{_render_default_yaml({"models": NEW_CONFIG_MODELS})}
cameras: {{}} # No cameras defined, UI wizard should be used
version: {CURRENT_CONFIG_VERSION}
"""
@@ -255,6 +260,15 @@ def verify_config_roles(camera_config: CameraConfig) -> None:
f"Camera {camera_config.name} has record enabled, but record is not assigned to an input."
)
if (
camera_config.record.enabled
and camera_config.record.sub.enabled
and "record_sub" not in assigned_roles
):
raise ValueError(
f"Camera {camera_config.name} has sub stream recording enabled, but record_sub is not assigned to an input."
)
if camera_config.audio.enabled and "audio" not in assigned_roles:
raise ValueError(
f"Camera {camera_config.name} has audio events enabled, but audio is not assigned to an input."
@@ -275,13 +289,11 @@ def verify_valid_live_stream_names(
)
def verify_recording_segments_setup_with_reasonable_time(
camera_config: CameraConfig,
def verify_record_output_args_segment_time(
camera_config: CameraConfig, output_args: str | list[str], role: str
) -> None:
"""Verify that recording segments are setup and segment time is not greater than 60."""
record_args: list[str] = get_ffmpeg_arg_list(
camera_config.ffmpeg.output_args.record
)
"""Verify that a recording role's output args segment at a reasonable time."""
record_args: list[str] = get_ffmpeg_arg_list(output_args)
if record_args[0].startswith("preset"):
return
@@ -291,16 +303,32 @@ def verify_recording_segments_setup_with_reasonable_time(
except ValueError:
raise ValueError(
f"Camera {camera_config.name} has no segment_time in \
recording output args, segment args are required for record."
{role} output args, segment args are required for record."
) from None
if int(record_args[seg_arg_index + 1]) > 60:
raise ValueError(
f"Camera {camera_config.name} has invalid segment_time output arg, \
f"Camera {camera_config.name} has invalid segment_time in {role} output args, \
segment_time must be 60 or less."
)
def verify_recording_segments_setup_with_reasonable_time(
camera_config: CameraConfig,
) -> None:
"""Verify that recording segments are setup and segment time is not greater than 60."""
verify_record_output_args_segment_time(
camera_config, camera_config.ffmpeg.output_args.record, "recording"
)
if camera_config.record.sub.enabled:
verify_record_output_args_segment_time(
camera_config,
camera_config.ffmpeg.output_args.effective_record_sub,
"sub stream recording",
)
def verify_zone_objects_are_tracked(camera_config: CameraConfig) -> None:
"""Verify that user has not entered zone objects that are not in the tracking config."""
for zone_name, zone in camera_config.zones.items():
@@ -497,16 +525,11 @@ class FrigateConfig(FrigateBaseModel):
description="User interface preferences such as timezone, time/date formatting, and units.",
)
# Detector config
detectors: dict[str, BaseDetectorConfig] = Field(
default=DEFAULT_DETECTORS,
title="Detector hardware",
description="Configuration for object detectors (CPU, GPU, ONNX backends) and any detector-specific model settings.",
)
model: ModelConfig = Field(
default_factory=ModelConfig,
title="Detection model",
description="Settings to configure a custom object detection model and its input shape.",
# Detection model config
models: list[ModelConfig] = Field(
default_factory=_default_models,
title="Detection models",
description="Object detection models and the hardware each one runs on. Cameras pick a model by matching their detect.scene against a model's scene.",
)
# GenAI config (named provider configs: name -> GenAIConfig)
@@ -621,11 +644,226 @@ class FrigateConfig(FrigateBaseModel):
)
_plus_api: PlusApi
_model_devices: dict[SceneEnum, list[DeviceSpec]]
_camera_models: dict[str, ModelConfig]
_all_attributes: list[str]
_all_attribute_logos: list[str]
_all_attributes_map: dict[str, list[str]]
_all_labels: set[str]
@property
def plus_api(self) -> PlusApi:
return self._plus_api
@property
def all_attributes(self) -> list[str]:
"""Every attribute label across all configured models."""
return self._all_attributes
@property
def all_attribute_logos(self) -> list[str]:
"""Every logo attribute label across all configured models."""
return self._all_attribute_logos
@property
def all_attributes_map(self) -> dict[str, list[str]]:
"""Object label to attribute labels, merged across all configured models."""
return self._all_attributes_map
@property
def all_labels(self) -> set[str]:
"""Every object label across all configured models."""
return self._all_labels
@property
def primary_model(self) -> ModelConfig:
"""The model used when no specific camera is in play."""
for model in self.models:
if model.scene == SceneEnum.all:
return model
return self.models[0]
def model_for_camera(self, camera_name: str) -> ModelConfig:
"""Get the detection model a camera runs on.
Cameras added at runtime (wizard, clone, debug replay) are inserted
into cameras after parse, so they miss the cache built during
post_validation and are resolved here on first lookup.
Args:
camera_name: Name of the camera
Returns:
The model matching the camera's detect scene
"""
model = self._camera_models.get(camera_name)
if model is None:
camera = self.cameras.get(camera_name)
scene = camera.detect.scene if camera is not None else SceneEnum.all
model = self._resolve_camera_model(camera_name, scene)
self._camera_models[camera_name] = model
return model
def drop_camera_model(self, camera_name: str) -> None:
"""Forget the cached model for a camera removed at runtime.
A later re-add resolves fresh, so a camera recreated under the same
name with a different detect scene doesn't inherit the removed
camera's model.
Args:
camera_name: Name of the removed camera
"""
self._camera_models.pop(camera_name, None)
def devices_for_model(self, model: ModelConfig) -> list[DeviceSpec]:
"""Get the parsed hardware devices a model runs on.
Args:
model: One of the configured models
Returns:
The parsed device specs, in config order
"""
return self._model_devices[model.scene]
def _load_model(self, model: ModelConfig, detector: str) -> ModelConfig:
"""Apply detector specific defaults to a model and load its weights and labels.
Args:
model: The configured model
detector: The detector type the model runs on
Returns:
The loaded model
"""
model_config = model.model_dump(exclude_unset=True, warnings="none")
if "path" not in model_config:
if detector == "cpu" or detector.endswith("_tfl"):
model_config["path"] = "/cpu_model.tflite"
elif detector == "edgetpu":
model_config["path"] = "/edgetpu_model.tflite"
elif detector == "openvino":
for default_key, default_value in DEFAULT_MODEL.items():
model_config.setdefault(default_key, default_value)
loaded = ModelConfig.model_validate(model_config)
loaded.check_and_load_plus_model(self.plus_api, detector)
loaded.compute_model_hash()
return loaded
def _load_models(self) -> None:
"""Validate the configured models and load each one."""
if not self.models:
raise ValueError("At least one model must be configured under models")
model_devices: dict[SceneEnum, list[DeviceSpec]] = {}
# device string -> the scene of the model that already claimed it
claimed_devices: dict[str, SceneEnum] = {}
for index, model in enumerate(self.models):
scene = model.scene.value
if model.scene in model_devices:
raise ValueError(
f"Multiple models are configured with a scene of '{scene}'. Each model must use a different scene."
)
if not model.devices:
raise ValueError(
f"Model '{scene}' must list at least one entry under devices."
)
try:
devices = [parse_device(device) for device in model.devices]
except DeviceParseError as err:
raise ValueError(
f"Model '{scene}' has an invalid device: {err}"
) from err
detectors = {device.detector for device in devices}
if len(detectors) > 1:
raise ValueError(
f"Model '{scene}' mixes the {', '.join(sorted(detectors))} detectors. All of a model's devices must use the same detector."
)
for device in devices:
if device.raw in claimed_devices and not device.shareable:
other = claimed_devices[device.raw]
where = (
f"twice by model '{scene}'"
if other == model.scene
else f"by both the '{other.value}' and '{scene}' models"
)
raise ValueError(
f"Device '{device.raw}' is used {where}, but it can only run one detection process."
)
claimed_devices[device.raw] = model.scene
self.models[index] = self._load_model(model, devices[0].detector)
model_devices[model.scene] = devices
attributes: set[str] = set()
attribute_logos: set[str] = set()
attributes_map: dict[str, set[str]] = {}
labels: set[str] = set()
for model in self.models:
attributes.update(model.all_attributes)
attribute_logos.update(model.all_attribute_logos)
labels.update(model.merged_labelmap.values())
for label, label_attributes in model.attributes_map.items():
attributes_map.setdefault(label, set()).update(label_attributes)
self._model_devices = model_devices
self._all_attributes = sorted(attributes)
self._all_attribute_logos = sorted(attribute_logos)
self._all_attributes_map = {
label: sorted(label_attributes)
for label, label_attributes in sorted(attributes_map.items())
}
self._all_labels = labels
def _resolve_camera_model(self, name: str, scene: SceneEnum) -> ModelConfig:
"""Resolve which model a camera runs on.
A camera may name a scene no model is configured for, which is valid as
long as an 'all' model is there to fall back to.
Args:
name: Name of the camera
scene: The camera's detect scene, which defaults to 'all'
Returns:
The model the camera runs on
"""
by_scene = {model.scene: model for model in self.models}
model = by_scene.get(scene)
if model is not None:
return model
default = by_scene.get(SceneEnum.all)
if default is None:
raise ValueError(
f"Camera '{name}' has a detect scene of '{scene.value}', but no model is configured for that scene or for 'all'."
)
logger.warning(
"Camera '%s' has a detect scene of '%s', but no model is configured for that scene, so the 'all' model is used",
name,
scene.value,
)
return default
@model_validator(mode="after")
def post_validation(self, info: ValidationInfo) -> Self:
# Load plus api from context, if possible.
@@ -670,8 +908,10 @@ class FrigateConfig(FrigateBaseModel):
"'embeddings' in its roles for semantic search."
)
self._load_models()
# set default min_score for object attributes
for attribute in self.model.all_attributes:
for attribute in self.all_attributes:
existing = self.objects.filters.get(attribute)
if existing is None:
self.objects.filters[attribute] = FilterConfig(min_score=0.7)
@@ -721,44 +961,7 @@ class FrigateConfig(FrigateBaseModel):
exclude_unset=True,
)
for key, detector in self.detectors.items():
adapter = TypeAdapter(DetectorConfig)
model_dict = (
detector
if isinstance(detector, dict)
else detector.model_dump(warnings="none")
)
detector_config: BaseDetectorConfig = adapter.validate_python(model_dict)
# users should not set model themselves
if detector_config.model:
logger.warning(
"The model key should be specified at the root level of the config, not under detectors. The nested model key will be ignored."
)
detector_config.model = None
model_config = self.model.model_dump(exclude_unset=True, warnings="none")
if detector_config.model_path:
model_config["path"] = detector_config.model_path
if "path" not in model_config:
if detector_config.type == "cpu" or detector_config.type.endswith(
"_tfl"
):
model_config["path"] = "/cpu_model.tflite"
elif detector_config.type == "edgetpu":
model_config["path"] = "/edgetpu_model.tflite"
elif detector_config.type == "openvino":
for default_key, default_value in DEFAULT_MODEL.items():
model_config.setdefault(default_key, default_value)
model = ModelConfig.model_validate(model_config)
model.check_and_load_plus_model(self.plus_api, detector_config.type)
model.compute_model_hash()
labelmap_objects = model.merged_labelmap.values()
detector_config.model = model
self.detectors[key] = detector_config
self._camera_models = {}
for name, camera in self.cameras.items():
modified_global_config = global_config.copy()
@@ -785,6 +988,9 @@ class FrigateConfig(FrigateBaseModel):
{"name": name, **merged_config}
)
camera_model = self._resolve_camera_model(name, camera_config.detect.scene)
self._camera_models[name] = camera_model
if camera_config.ffmpeg.hwaccel_args == "auto":
camera_config.ffmpeg.hwaccel_args = self.ffmpeg.hwaccel_args
@@ -1005,7 +1211,7 @@ class FrigateConfig(FrigateBaseModel):
verify_profile_overrides_match_base(camera_config)
verify_autotrack_zones(camera_config)
verify_motion_and_detect(camera_config)
verify_objects_track(camera_config, labelmap_objects)
verify_objects_track(camera_config, camera_model.merged_labelmap.values())
verify_lpr_and_face(self, camera_config)
# Validate camera profiles reference top-level profile definitions
@@ -1022,8 +1228,16 @@ class FrigateConfig(FrigateBaseModel):
config.name = name
self.objects.parse_all_objects(self.cameras)
self.model.create_colormap(sorted(self.objects.all_objects))
self.model.check_and_load_plus_model(self.plus_api)
# every model shares one colormap so a label is drawn the same color no
# matter which model detected it, so filter attributes across all models
# rather than letting each model filter with only its own
colored_labels = sorted(
set(self.objects.all_objects) - set(self.all_attributes)
)
for model in self.models:
model.create_colormap(colored_labels)
# Check audio transcription and audio detection requirements
if self.audio_transcription.enabled:
@@ -1093,6 +1307,9 @@ class FrigateConfig(FrigateBaseModel):
@classmethod
def parse(cls, config, *, is_json=None, safe_load=False, **context):
# Pick up secrets.yaml edits without a restart.
reload_sources()
# If config is a file, read its contents.
if hasattr(config, "read"):
fname = getattr(config, "name", None)
+192 -18
View File
@@ -1,20 +1,193 @@
"""Environment variable and secrets handling for the Frigate config."""
import logging
import os
import re
from collections.abc import Mapping
from pathlib import Path
from typing import Annotated
from typing import Annotated, Any
from pydantic import AfterValidator, ValidationInfo
from ruamel.yaml import YAML, YAMLError
FRIGATE_ENV_VARS = {k: v for k, v in os.environ.items() if k.startswith("FRIGATE_")}
secrets_dir = os.environ.get("CREDENTIALS_DIRECTORY", "/run/secrets")
# read secret files as env vars too
if os.path.isdir(secrets_dir) and os.access(secrets_dir, os.R_OK):
for secret_file in os.listdir(secrets_dir):
if secret_file.startswith("FRIGATE_"):
FRIGATE_ENV_VARS[secret_file] = (
Path(os.path.join(secrets_dir, secret_file)).read_text().strip()
from frigate.const import CONFIG_DIR
logger = logging.getLogger(__name__)
class UnknownVariableError(ValueError):
"""Undefined {FRIGATE_*} placeholder. ValueError so pydantic names the field."""
# Substitution sources, lowest precedence first.
_CONFIG_ENV_VARS: dict[str, str] = {}
_SECRETS_FILE: dict[str, str] = {}
# Snapshot: apply_config_env_vars() writes os.environ after import.
_CONTAINER_ENV: dict[str, str] = {
k: v for k, v in os.environ.items() if k.startswith("FRIGATE_")
}
_CREDENTIALS_DIR: dict[str, str] = {}
_SOURCES: tuple[tuple[str, dict[str, str]], ...] = (
("environment_vars config block", _CONFIG_ENV_VARS),
("secrets.yaml", _SECRETS_FILE),
("container environment", _CONTAINER_ENV),
("credentials directory", _CREDENTIALS_DIR),
)
FRIGATE_ENV_VARS: dict[str, str] = {}
_WARNED_COLLISIONS: set[str] = set()
def _rebuild(warn: bool = True) -> None:
"""Merge the sources into FRIGATE_ENV_VARS.
warn=False is for the import-time call, before logging is configured.
"""
merged: dict[str, str] = {}
origin: dict[str, str] = {}
duplicated: set[str] = set()
for label, source in _SOURCES:
for key, value in source.items():
if key in merged and merged[key] != value:
duplicated.add(key)
merged[key] = value
origin[key] = label
if warn:
for key in sorted(duplicated - _WARNED_COLLISIONS):
_WARNED_COLLISIONS.add(key)
logger.warning(
"%s is defined in more than one place, using the value from %s",
key,
origin[key],
)
# In place: tests hold a reference to this dict.
FRIGATE_ENV_VARS.clear()
FRIGATE_ENV_VARS.update(merged)
def _load_credentials_dir() -> dict[str, str]:
"""Read FRIGATE_* files from the Docker or systemd credentials directory."""
directory = os.environ.get("CREDENTIALS_DIRECTORY", "/run/secrets")
values: dict[str, str] = {}
if not (os.path.isdir(directory) and os.access(directory, os.R_OK)):
return values
for name in os.listdir(directory):
if not name.startswith("FRIGATE_"):
continue
try:
values[name] = Path(os.path.join(directory, name)).read_text().strip()
except (OSError, UnicodeDecodeError):
logger.warning("Unable to read %s in %s, skipping", name, directory)
return values
def _secrets_file_path() -> str | None:
"""Locate secrets.yaml next to the config file."""
config_file = os.environ.get("CONFIG_FILE")
config_dir = os.path.dirname(config_file) if config_file else CONFIG_DIR
for name in ("secrets.yaml", "secrets.yml"):
path = os.path.join(config_dir, name)
if os.path.isfile(path):
return path
return None
def _load_secrets_file() -> dict[str, str]:
"""Read the flat FRIGATE_* map from secrets.yaml, if it exists."""
path = _secrets_file_path()
if path is None:
return {}
try:
with open(path) as f:
raw: Any = YAML(typ="safe").load(f)
except OSError as err:
raise ValueError(f"Unable to read {path}: {err.strerror}") from err
except YAMLError as err:
# The parser message can quote values, so only name a position.
mark = getattr(err, "problem_mark", None)
where = f" near line {mark.line + 1}" if mark is not None else ""
raise ValueError(f"{path} is not valid YAML{where}") from err
if raw is None:
return {}
if not isinstance(raw, dict):
raise ValueError(f"{path} must be a flat map of names to values")
values: dict[str, str] = {}
for key, value in raw.items():
name = str(key)
if isinstance(value, (dict, list)):
raise ValueError(f"{path} value for {name} must be a single value")
if not name.startswith("FRIGATE_"):
logger.warning(
"Ignoring %s in %s, names must start with FRIGATE_", name, path
)
continue
values[name] = "" if value is None else str(value)
return values
def reload_sources(warn: bool = True) -> None:
"""Re-read the file backed sources and rebuild the namespace."""
_CREDENTIALS_DIR.clear()
_CREDENTIALS_DIR.update(_load_credentials_dir())
try:
secrets = _load_secrets_file()
except ValueError as err:
# Keep the last good values; this runs at import and on every parse.
logger.error("Ignoring secrets file, %s", err)
else:
_SECRETS_FILE.clear()
_SECRETS_FILE.update(secrets)
_rebuild(warn)
def apply_config_env_vars(values: Mapping[str, object]) -> None:
"""Install the environment_vars block as the lowest priority source.
Unprefixed keys only set os.environ.
"""
for key, value in values.items():
resolved = str(value)
if key.startswith("FRIGATE_"):
_CONFIG_ENV_VARS[key] = resolved
else:
os.environ[key] = resolved
_rebuild()
# Export the winning value; auth reads FRIGATE_JWT_SECRET from os.environ.
for key in values:
if key.startswith("FRIGATE_"):
os.environ[key] = FRIGATE_ENV_VARS[key]
reload_sources(warn=False)
# Matches a FRIGATE_* identifier following an opening brace.
_FRIGATE_IDENT_RE = re.compile(r"FRIGATE_[A-Za-z0-9_]+")
@@ -29,12 +202,13 @@ def substitute_frigate_vars(value: str) -> str:
* `{{` and `}}` collapse to literal `{` / `}` (the documented escape).
* `{FRIGATE_NAME}` is replaced from `FRIGATE_ENV_VARS`; an unknown name
raises `KeyError` to preserve the existing "Invalid substitution"
error path.
raises `UnknownVariableError` to preserve the existing "Invalid
substitution" error path.
* A `{` that begins `{FRIGATE_` but is not a well-formed
`{FRIGATE_NAME}` placeholder raises `ValueError` (malformed
placeholder). Callers that catch `KeyError` to allow unknown-var
passthrough will still surface malformed syntax as an error.
placeholder). Callers that catch `UnknownVariableError` to allow
unknown-var passthrough will still surface malformed syntax as an
error.
* Any other `{` or `}` is treated as a literal and passed through.
"""
out: list[str] = []
@@ -58,7 +232,10 @@ def substitute_frigate_vars(value: str) -> str:
):
key = ident_match.group(0)
if key not in FRIGATE_ENV_VARS:
raise KeyError(key)
raise UnknownVariableError(
f"{key} is not defined in the environment, "
"secrets.yaml, or the environment_vars config"
)
out.append(FRIGATE_ENV_VARS[key])
i = ident_match.end() + 1
continue
@@ -94,10 +271,7 @@ EnvString = Annotated[str, AfterValidator(validate_env_string)]
def validate_env_vars(v: dict[str, str], info: ValidationInfo) -> dict[str, str]:
if isinstance(info.context, dict) and info.context.get("install", False):
for k, val in v.items():
os.environ[k] = val
if k.startswith("FRIGATE_"):
FRIGATE_ENV_VARS[k] = val
apply_config_env_vars(v)
return v
+7 -2
View File
@@ -8,6 +8,7 @@ from datetime import UTC, datetime
from pathlib import Path
from typing import Any
from frigate.config.camera.birdseye import birdseye_modes_to_mqtt_payload
from frigate.config.camera.updater import (
CameraConfigUpdateEnum,
CameraConfigUpdatePublisher,
@@ -42,8 +43,12 @@ SECTION_STATE_TOPICS: dict[str, list[tuple[str, Callable[[Any], Any]]]] = {
"birdseye": [
("birdseye", lambda c: "ON" if c.birdseye.enabled else "OFF"),
(
"birdseye_mode",
lambda c: c.birdseye.mode.value.upper() if c.birdseye.enabled else "OFF",
"birdseye_modes",
lambda c: (
birdseye_modes_to_mqtt_payload(c.birdseye.modes)
if c.birdseye.enabled
else "OFF"
),
),
],
"detect": [("detect", lambda c: "ON" if c.detect.enabled else "OFF")],
+6
View File
@@ -23,6 +23,12 @@ SHM_FRAMES_VAR = "SHM_MAX_FRAMES"
REDACTED_CREDENTIAL_SENTINEL = "__FRIGATE_SAVED_CREDENTIAL__"
# Stream type constants
STREAM_TYPE_MAIN = "main"
STREAM_TYPE_SUB = "sub"
SUB_CACHE_TAG = "@sub"
# Attribute & Object constants
DEFAULT_ATTRIBUTE_LABEL_MAP = {
@@ -72,7 +72,7 @@ class LicensePlateProcessingMixin:
# Object config
self.lp_objects: list[str] = []
for obj, attributes in self.config.model.attributes_map.items():
for obj, attributes in self.config.all_attributes_map.items():
if "license_plate" in attributes:
self.lp_objects.append(obj)
@@ -83,6 +83,10 @@ class AudioTranscriptionPostProcessor(PostProcessorApi):
"""
event_id = data["event_id"]
camera_name = data["camera"]
camera_config = self.config.cameras.get(camera_name)
if camera_config is None:
return
if data_type == PostProcessDataEnum.recording:
start_ts = data["frame_time"]
@@ -104,7 +108,7 @@ class AudioTranscriptionPostProcessor(PostProcessorApi):
try:
audio_data = get_audio_from_recording(
self.config.cameras[camera_name].ffmpeg,
camera_config.ffmpeg,
camera_name,
start_ts,
end_ts,
@@ -151,7 +151,12 @@ class ObjectDescriptionProcessor(PostProcessorApi):
logger.error(f"Event {event_id} not found for description regeneration")
return
camera_config = self.config.cameras[str(event.camera)]
camera_config = self.config.cameras.get(str(event.camera))
if camera_config is None:
logger.error("Camera %s no longer exists", event.camera)
return
if not camera_config.objects.genai.enabled and not force:
logger.error(f"GenAI not enabled for camera {event.camera}")
return
@@ -137,7 +137,10 @@ class ReviewDescriptionProcessor(PostProcessorApi):
return
camera = data["after"]["camera"]
camera_config = self.config.cameras[camera]
camera_config = self.config.cameras.get(camera)
if camera_config is None:
return
if not camera_config.review.genai.enabled:
return
@@ -231,8 +234,8 @@ class ReviewDescriptionProcessor(PostProcessorApi):
final_data,
thumbs,
camera_config.review.genai,
list(self.config.model.merged_labelmap.values()),
self.config.model.all_attributes,
sorted(self.config.all_labels),
self.config.all_attributes,
),
).start()
+34 -5
View File
@@ -3,7 +3,7 @@ import json
import logging
import os
from enum import Enum
from typing import Any
from typing import Any, ClassVar
import requests
from pydantic import BaseModel, ConfigDict, Field
@@ -15,6 +15,9 @@ from frigate.util.builtin import generate_color_palette, load_labels
logger = logging.getLogger(__name__)
# attributes that are recognized rather than shown as a logo
NON_LOGO_ATTRIBUTES = ["face", "license_plate"]
class PixelFormatEnum(str, Enum):
rgb = "rgb"
@@ -44,7 +47,27 @@ class ModelTypeEnum(str, Enum):
yologeneric = "yolo-generic"
class SceneEnum(str, Enum):
"""The camera environment a detection model is intended for."""
all = "all"
indoor = "indoor"
outdoor = "outdoor"
indoor_thermal = "indoor_thermal"
outdoor_thermal = "outdoor_thermal"
class ModelConfig(BaseModel):
scene: SceneEnum = Field(
default=SceneEnum.all,
title="Model scene",
description="The camera environment this model is used for. Cameras select a model by setting detect.scene to a matching value, and 'all' is used by any camera that does not set one.",
)
devices: list[str] = Field(
default_factory=list,
title="Detection hardware",
description="Hardware this model runs on, as '<detector>' or '<detector>:<device>' (for example 'edgetpu:pci:0' or 'openvino:GPU'). Listing the same device more than once runs additional inference processes on it.",
)
path: str | None = Field(
None,
title="Custom object detector model path",
@@ -111,7 +134,7 @@ class ModelConfig(BaseModel):
@property
def non_logo_attributes(self) -> list[str]:
return ["face", "license_plate"]
return NON_LOGO_ATTRIBUTES
@property
def all_attributes(self) -> list[str]:
@@ -201,9 +224,7 @@ class ModelConfig(BaseModel):
unique_attributes.update(attributes)
self._all_attributes = list(unique_attributes)
self._all_attribute_logos = list(
unique_attributes - set(["face", "license_plate"])
)
self._all_attribute_logos = list(unique_attributes - set(NON_LOGO_ATTRIBUTES))
self._merged_labelmap = {
**{int(key): val for key, val in model_info["labelMap"].items()},
@@ -234,6 +255,14 @@ class ModelConfig(BaseModel):
class BaseDetectorConfig(BaseModel):
# how the trailing part of a device string ("openvino:GPU" -> "GPU") maps onto
# this detector's fields, and whether the same device may be listed more than
# once to run additional inference processes against it. Most accelerators
# multiplex fine, so this is opt-out rather than opt-in.
device_spec_field: ClassVar[str] = "device"
device_spec_type: ClassVar[type] = str
shareable: ClassVar[bool] = True
# the type field must be defined in all subclasses
type: str = Field(
default="cpu",
+19 -1
View File
@@ -2,7 +2,7 @@ import importlib
import logging
import pkgutil
from enum import Enum
from typing import Annotated, Union
from typing import Annotated, Union, get_args
from pydantic import Field
@@ -39,3 +39,21 @@ DetectorConfig = Annotated[
Union[tuple(BaseDetectorConfig.__subclasses__())], # noqa: UP007
Field(discriminator="type"),
]
def _discriminator_value(config_class: type[BaseDetectorConfig]) -> str | None:
"""Read the Literal value of a detector config class' type field."""
field = config_class.model_fields.get("type")
if field is None:
return None
values = get_args(field.annotation)
return values[0] if values else None
config_types: dict[str, type[BaseDetectorConfig]] = {
key: config_class
for config_class in BaseDetectorConfig.__subclasses__()
if (key := _discriminator_value(config_class)) is not None
}
+113
View File
@@ -0,0 +1,113 @@
"""Parsing of detection hardware device strings."""
import logging
from dataclasses import dataclass
from pydantic import TypeAdapter, ValidationError
from frigate.detectors.detector_config import BaseDetectorConfig, ModelConfig
from frigate.detectors.detector_types import DetectorConfig, config_types
logger = logging.getLogger(__name__)
_detector_adapter: TypeAdapter[BaseDetectorConfig] = TypeAdapter(DetectorConfig)
@dataclass(frozen=True)
class DeviceSpec:
"""A parsed `<detector>` or `<detector>:<device>` string."""
raw: str
detector: str
device: str | None
@property
def shareable(self) -> bool:
"""Whether this device may be listed more than once."""
return config_types[self.detector].shareable
class DeviceParseError(ValueError):
pass
def parse_device(raw: str) -> DeviceSpec:
"""Parse a device string into its detector type and detector specific device.
Args:
raw: The configured device string, for example 'edgetpu:pci:0'
Returns:
The parsed spec
Raises:
DeviceParseError: If the detector type is unknown or the device is not
valid for that detector
"""
detector, separator, device = raw.partition(":")
if detector not in config_types:
raise DeviceParseError(
f"'{raw}' does not name a known detector. Available detectors are {', '.join(sorted(config_types))}"
)
spec = DeviceSpec(raw=raw, detector=detector, device=device if separator else None)
# surface a bad device now rather than when the detection process starts
build_detector_config(spec, None)
return spec
def build_detector_config(
spec: DeviceSpec, model: ModelConfig | None
) -> BaseDetectorConfig:
"""Build the detector config a device string describes.
Args:
spec: The parsed device spec
model: The model this detector runs, if it has been resolved yet
Returns:
The validated detector config
Raises:
DeviceParseError: If the device is not valid for this detector type
"""
config: dict[str, object] = {"type": spec.detector, "model": model}
if spec.device is not None:
config_class = config_types[spec.detector]
try:
config[config_class.device_spec_field] = config_class.device_spec_type(
spec.device
)
except ValueError as err:
raise DeviceParseError(
f"'{spec.raw}' is not a valid {spec.detector} device: {err}"
) from err
try:
return _detector_adapter.validate_python(config)
except ValidationError as err:
raise DeviceParseError(f"'{spec.raw}' is not a valid device: {err}") from err
def runner_names(devices: list[DeviceSpec]) -> list[str]:
"""Build a unique name for each device, since a shareable device may repeat.
Args:
devices: Every device spec across every configured model, in config order
Returns:
A name per device, suffixed with '#2', '#3', etc. on repeats
"""
names: list[str] = []
seen: dict[str, int] = {}
for spec in devices:
count = seen.get(spec.raw, 0) + 1
seen[spec.raw] = count
names.append(spec.raw if count == 1 else f"{spec.raw}#{count}")
return names
+368
View File
@@ -0,0 +1,368 @@
"""Discovery of object detection hardware attached to the system.
Every probe here is a filesystem read. Nothing shells out, initializes a
runtime, or opens a device, so this is cheap enough to run from the API process
while detector children hold the hardware.
Hardware is reported whether or not this image ships a detector that can drive
it. Matching hardware to an image is a separate concern.
"""
import logging
import os
from glob import glob
from pydantic import BaseModel, Field
from frigate.const import SUPPORTED_RK_SOCS
from frigate.detectors.detector_types import config_types
from frigate.util.services import enumerate_drm_devices
logger = logging.getLogger(__name__)
# roots the probes read from, so tests can point them at a fixture tree
SYS_ROOT = "/sys"
DEV_ROOT = "/dev"
PROC_ROOT = "/proc"
ETC_ROOT = "/etc"
# a Coral reports as Global Unichip until its firmware is loaded, then as Google
CORAL_USB_IDS = {("1a6e", "089a"), ("18d1", "9302")}
INTEL_DRM_DRIVERS = ("i915", "xe")
AMD_DRM_DRIVERS = ("amdgpu",)
class HardwareUnit(BaseModel):
"""One physical piece of hardware."""
device: str = Field(
title="Device string",
description="The value to put in a model's devices list, for example 'edgetpu:pci:1'.",
)
label: str = Field(
title="Unit label",
description="How to identify this unit among others of the same kind, for example 'PCIe 1'.",
)
class DetectionHardware(BaseModel):
"""A kind of detection hardware, and every unit of it that was found."""
key: str = Field(
title="Hardware key",
description="Stable identifier for this kind of hardware.",
)
detector: str = Field(
title="Detector type",
description="The detector that drives this hardware.",
)
name: str = Field(
title="Hardware name",
description="Human readable name for this kind of hardware.",
)
units: list[HardwareUnit] = Field(
title="Units",
description="Each physical piece of this hardware that was found.",
)
count: int = Field(
title="Unit count",
description="How many units were found.",
)
unlimited: bool = Field(
title="Unlimited detectors",
description="Whether this hardware can run more inference processes than there are units.",
)
def _read(path: str) -> str | None:
"""Read a small file, returning None if it cannot be read."""
try:
with open(path) as f:
return f.read().strip()
except OSError:
return None
def _is_shareable(detector: str) -> bool:
"""Whether a detector lets the same device run more than one process."""
config_class = config_types.get(detector)
# a detector missing from this image is assumed to behave like most of them
return config_class.shareable if config_class else True
def _hardware(
key: str, detector: str, name: str, units: list[HardwareUnit]
) -> DetectionHardware:
return DetectionHardware(
key=key,
detector=detector,
name=name,
units=units,
count=len(units),
unlimited=_is_shareable(detector),
)
def detect_coral_pci() -> DetectionHardware | None:
"""Find PCIe and M.2 Coral accelerators, which register as apex devices."""
names = sorted(
os.path.basename(path) for path in glob(f"{SYS_ROOT}/class/apex/apex_*")
)
if not names:
return None
units = [
HardwareUnit(device=f"edgetpu:pci:{index}", label=f"PCIe {index}")
for index in range(len(names))
]
return _hardware("edgetpu:pci", "edgetpu", "Coral EdgeTPU (PCIe)", units)
def detect_coral_usb() -> DetectionHardware | None:
"""Find USB Coral accelerators by their USB vendor and product ids."""
found = 0
for device_dir in sorted(glob(f"{SYS_ROOT}/bus/usb/devices/*")):
vendor = _read(os.path.join(device_dir, "idVendor"))
product = _read(os.path.join(device_dir, "idProduct"))
if vendor and product and (vendor.lower(), product.lower()) in CORAL_USB_IDS:
found += 1
if not found:
return None
units = [
HardwareUnit(device=f"edgetpu:usb:{index}", label=f"USB {index}")
for index in range(found)
]
return _hardware("edgetpu:usb", "edgetpu", "Coral EdgeTPU (USB)", units)
def _drm_devices(drivers: tuple[str, ...]) -> list[str]:
"""PCI addresses of DRM devices bound to one of the given drivers."""
return sorted(
pdev for pdev, driver in enumerate_drm_devices().items() if driver in drivers
)
def detect_intel_gpu() -> DetectionHardware | None:
"""Find Intel GPUs through their DRM driver."""
pdevs = _drm_devices(INTEL_DRM_DRIVERS)
if not pdevs:
return None
# OpenVINO reports a lone GPU as "GPU" and enumerates them as GPU.0, GPU.1
# only when there is more than one
if len(pdevs) == 1:
units = [HardwareUnit(device="openvino:GPU", label=pdevs[0])]
else:
units = [
HardwareUnit(device=f"openvino:GPU.{index}", label=pdev)
for index, pdev in enumerate(pdevs)
]
return _hardware("openvino:GPU", "openvino", "Intel GPU", units)
def detect_intel_npu() -> DetectionHardware | None:
"""Find Intel NPUs, which register as accel devices bound to intel_vpu."""
units = []
for accel_path in sorted(glob(f"{SYS_ROOT}/class/accel/accel*")):
try:
driver = os.path.basename(os.readlink(f"{accel_path}/device/driver"))
except OSError:
continue
if driver != "intel_vpu":
continue
units.append(
HardwareUnit(device="openvino:NPU", label=os.path.basename(accel_path))
)
if not units:
return None
# OpenVINO has no way to address a specific NPU, so only the first is usable
return _hardware("openvino:NPU", "openvino", "Intel NPU", units[:1])
def detect_amd_gpu() -> DetectionHardware | None:
"""Find AMD GPUs through their DRM driver."""
pdevs = _drm_devices(AMD_DRM_DRIVERS)
if not pdevs:
return None
# ROCm runs through onnx, whose MIGraphX provider takes no device index, so
# only one is addressable
units = [HardwareUnit(device="onnx", label=pdevs[0])]
return _hardware("onnx:amd", "onnx", "AMD GPU", units)
def detect_nvidia_gpu() -> DetectionHardware | None:
"""Find discrete Nvidia GPUs through the nvidia driver's proc entries."""
units = []
for index, gpu_dir in enumerate(sorted(glob(f"{PROC_ROOT}/driver/nvidia/gpus/*"))):
information = _read(os.path.join(gpu_dir, "information")) or ""
name = f"GPU {index}"
for line in information.splitlines():
if line.startswith("Model:"):
name = line.split(":", 1)[1].strip()
break
units.append(HardwareUnit(device=f"onnx:{index}", label=name))
if not units:
return None
# the model name is more useful as the hardware name when there is only one
name = units[0].label if len(units) == 1 else "NVIDIA GPU"
return _hardware("onnx:nvidia", "onnx", name, units)
def detect_jetson() -> DetectionHardware | None:
"""Find an Nvidia Jetson, whose integrated GPU runs through tensorrt."""
is_jetson = os.path.isfile(f"{ETC_ROOT}/nv_tegra_release") or os.path.exists(
f"{SYS_ROOT}/devices/gpu.0/load"
)
if not is_jetson:
return None
units = [HardwareUnit(device="tensorrt:0", label="Integrated GPU")]
return _hardware("tensorrt", "tensorrt", "NVIDIA Jetson", units)
def _dev_units(pattern: str, device: str, label: str) -> list[HardwareUnit]:
"""Build units from device nodes matching a glob."""
return [
HardwareUnit(device=device.format(index=index), label=f"{label} {index}")
for index in range(len(glob(f"{DEV_ROOT}/{pattern}")))
]
def detect_hailo() -> DetectionHardware | None:
"""Find Hailo accelerators by their device nodes."""
nodes = sorted(glob(f"{DEV_ROOT}/hailo*"))
if not nodes:
return None
# the hailo runtime schedules across every attached device itself, so there
# is nothing to address individually
units = [HardwareUnit(device="hailo8l:PCIe", label=os.path.basename(nodes[0]))]
return _hardware("hailo8l", "hailo8l", "Hailo", units)
def detect_memryx() -> DetectionHardware | None:
"""Find MemryX accelerators by their device nodes."""
units = _dev_units("memx*", "memryx:PCIe:{index}", "PCIe")
if not units:
return None
return _hardware("memryx", "memryx", "MemryX MX3", units)
def detect_rockchip() -> DetectionHardware | None:
"""Find a Rockchip NPU by reading the SoC from the device tree."""
compatible = _read(f"{PROC_ROOT}/device-tree/compatible")
if not compatible:
return None
soc = compatible.split(",")[-1].strip("\x00")
if soc not in SUPPORTED_RK_SOCS:
return None
units = [HardwareUnit(device="rknn", label=soc.upper())]
return _hardware("rknn", "rknn", f"Rockchip NPU ({soc.upper()})", units)
def detect_axengine() -> DetectionHardware | None:
"""Find an AXERA accelerator by its control device node."""
if not os.path.exists(f"{DEV_ROOT}/axcl_host"):
return None
units = [HardwareUnit(device="axengine", label="AXERA")]
return _hardware("axengine", "axengine", "AXERA NPU", units)
def detect_synaptics() -> DetectionHardware | None:
"""Find a Synaptics NPU by its device node."""
if not os.path.exists(f"{DEV_ROOT}/synap"):
return None
units = [HardwareUnit(device="synaptics", label="Synaptics")]
return _hardware("synaptics", "synaptics", "Synaptics NPU", units)
def detect_cpu() -> DetectionHardware:
"""The CPU, which is always available."""
units = [HardwareUnit(device="cpu", label="CPU")]
return _hardware("cpu", "cpu", "CPU", units)
# ordered so accelerators are offered ahead of the CPU fallback
PROBES = (
detect_coral_pci,
detect_coral_usb,
detect_hailo,
detect_memryx,
detect_intel_npu,
detect_intel_gpu,
detect_nvidia_gpu,
detect_jetson,
detect_amd_gpu,
detect_rockchip,
detect_axengine,
detect_synaptics,
detect_cpu,
)
class HardwareProber:
"""Probes for detection hardware, caching the result for the process."""
_hardware: list[DetectionHardware] | None = None
def probe(self, refresh: bool = False) -> list[DetectionHardware]:
"""Get the detection hardware attached to this system.
Args:
refresh: Probe again instead of using the cached result
Returns:
Every kind of detection hardware that was found
"""
if self._hardware is not None and not refresh:
return self._hardware
found = []
for probe in PROBES:
try:
hardware = probe()
except Exception:
logger.warning("Failed to probe for %s", probe.__name__, exc_info=True)
continue
if hardware is not None:
found.append(hardware)
logger.debug("Detected hardware: %s", [h.key for h in found])
self._hardware = found
return found
hardware_prober = HardwareProber()
+4 -1
View File
@@ -1,5 +1,5 @@
import logging
from typing import Literal
from typing import ClassVar, Literal
from pydantic import ConfigDict, Field
@@ -27,6 +27,9 @@ class CpuDetectorConfig(BaseDetectorConfig):
title="CPU",
)
device_spec_field: ClassVar[str] = "num_threads"
device_spec_type: ClassVar[type] = int
type: Literal[DETECTOR_KEY]
num_threads: int = Field(
default=3,
+4 -1
View File
@@ -1,7 +1,7 @@
import logging
import math
import os
from typing import Literal
from typing import ClassVar, Literal
import cv2
import numpy as np
@@ -28,6 +28,9 @@ class EdgeTpuDetectorConfig(BaseDetectorConfig):
title="EdgeTPU",
)
# a TPU can only be opened by one process
shareable: ClassVar[bool] = False
type: Literal[DETECTOR_KEY]
device: str = Field(
default=None,
+4 -1
View File
@@ -5,7 +5,7 @@ import shutil
import urllib.request
import zipfile
from queue import Queue
from typing import Literal
from typing import ClassVar, Literal
import cv2
import numpy as np
@@ -37,6 +37,9 @@ class MemryXDetectorConfig(BaseDetectorConfig):
title="MemryX",
)
# an accelerator can only be opened by one process
shareable: ClassVar[bool] = False
type: Literal[DETECTOR_KEY]
device: str = Field(
default="PCIe",
+1 -1
View File
@@ -28,7 +28,7 @@ class OvDetectorConfig(BaseDetectorConfig):
type: Literal[DETECTOR_KEY]
device: str = Field(
default=None,
default="AUTO",
title="Device Type",
description="The device to use for OpenVINO inference (e.g. 'CPU', 'GPU', 'NPU').",
)
+4 -1
View File
@@ -2,7 +2,7 @@ import logging
import os.path
import re
import urllib.request
from typing import Literal
from typing import ClassVar, Literal
import cv2
import numpy as np
@@ -35,6 +35,9 @@ class RknnDetectorConfig(BaseDetectorConfig):
title="RKNN",
)
device_spec_field: ClassVar[str] = "num_cores"
device_spec_type: ClassVar[type] = int
type: Literal[DETECTOR_KEY]
num_cores: int = Field(
default=0,
+3 -1
View File
@@ -14,7 +14,7 @@ try:
except ModuleNotFoundError:
TRT_SUPPORT = False
from typing import Literal
from typing import ClassVar, Literal
from pydantic import ConfigDict, Field
@@ -53,6 +53,8 @@ class TensorRTDetectorConfig(BaseDetectorConfig):
title="TensorRT",
)
device_spec_type: ClassVar[type] = int
type: Literal[DETECTOR_KEY]
device: int = Field(
default=0, title="GPU Device Index", description="The GPU device index to use."
+20 -1
View File
@@ -609,6 +609,18 @@ class EmbeddingMaintainer(threading.Thread):
# Embed the thumbnail
self._embed_thumbnail(event_id, thumbnail)
# every post processor below reads config.cameras[camera], but
# tracked_events still has to be released or the thumbnails held
# for this event leak, same as the two exits above
if camera not in self.config.cameras:
logger.debug("Skipping post processing for removed camera %s", camera)
for processor in self.post_processors:
if isinstance(processor, ObjectDescriptionProcessor):
processor.cleanup_event(event_id)
continue
# call any defined post processors
for processor in self.post_processors:
if isinstance(processor, LicensePlatePostProcessor):
@@ -666,11 +678,18 @@ class EmbeddingMaintainer(threading.Thread):
to_remove = []
for id, data in self.detected_license_plates.items():
camera_config = self.config.cameras.get(data["camera"])
if camera_config is None:
# camera was removed, drop the entry rather than expiring it
to_remove.append(id)
continue
last_seen = data.get("last_seen", 0)
if not last_seen:
continue
if now - last_seen > self.config.cameras[data["camera"]].lpr.expire_time:
if now - last_seen > camera_config.lpr.expire_time:
to_remove.append(id)
for id in to_remove:
self.event_metadata_publisher.publish(
+29 -7
View File
@@ -210,7 +210,11 @@ class AudioEventMaintainer(threading.Thread):
# per-camera stop signal so a single maintainer can be torn down at
# runtime (e.g. on camera removal) without stopping the whole process
self.camera_stop_event = threading.Event()
self.detector = AudioTfl(stop_event, self.camera_config.audio.num_threads)
self.detector = AudioTfl(
stop_event,
self.camera_config.audio.num_threads,
self.camera_config.audio.labelmap,
)
self.shape = (int(round(AUDIO_DURATION * AUDIO_SAMPLE_RATE)),)
self.chunk_size = int(round(AUDIO_DURATION * AUDIO_SAMPLE_RATE * 2))
self.logger = logging.getLogger(f"audio.{self.camera_config.name}")
@@ -392,7 +396,10 @@ class AudioEventMaintainer(threading.Thread):
while not self.stop_event.is_set() and not self.camera_stop_event.is_set():
# check if there is an updated config
self.config_subscriber.check_for_updates()
updated_topics = self.config_subscriber.check_for_updates()
if CameraConfigUpdateEnum.audio.name in updated_topics:
self.detector.update_labelmap(self.camera_config.audio.labelmap)
enabled = self.camera_config.enabled
if enabled != self.was_enabled:
@@ -451,10 +458,17 @@ class AudioEventMaintainer(threading.Thread):
class AudioTfl:
def __init__(self, stop_event: threading.Event, num_threads: int = 2) -> None:
def __init__(
self,
stop_event: threading.Event,
num_threads: int = 2,
labelmap: dict[int, str] | None = None,
) -> None:
self.stop_event = stop_event
self.num_threads = num_threads
self.labels = load_labels("/audio-labelmap.txt", prefill=521)
self._default_labels = load_labels("/audio-labelmap.txt", prefill=521)
self.labels: dict[int, str] = {}
self.update_labelmap(labelmap or {})
# Suppress TFLite delegate creation messages that bypass Python logging
with suppress_stderr_during("tflite_interpreter_init"):
self.interpreter = Interpreter(
@@ -466,6 +480,10 @@ class AudioTfl:
self.tensor_input_details = self.interpreter.get_input_details()
self.tensor_output_details = self.interpreter.get_output_details()
def update_labelmap(self, labelmap: dict[int, str]) -> None:
"""Merge configured label overrides into the default audio labelmap."""
self.labels = {**self._default_labels, **labelmap}
def _detect_raw(self, tensor_input: np.ndarray) -> np.ndarray:
self.interpreter.set_tensor(self.tensor_input_details[0]["index"], tensor_input)
self.interpreter.invoke()
@@ -504,10 +522,14 @@ class AudioTfl:
raw_detections = self._detect_raw(tensor_input)
detected_labels: set[str] = set()
for d in raw_detections:
if d[1] < threshold:
break
detections.append(
(self.labels[int(d[0])], float(d[1]), (d[2], d[3], d[4], d[5]))
)
label = self.labels[int(d[0])]
if label in detected_labels:
continue
detected_labels.add(label)
detections.append((label, float(d[1]), (d[2], d[3], d[4], d[5])))
return detections
+8 -8
View File
@@ -197,9 +197,11 @@ class EventCleanup(threading.Thread):
def expire_clips(self) -> list[str]:
## Expire events from unlisted cameras based on the global config
# effective days cover the sub window, keeping tracked objects in
# Explore while sub recordings and review items still exist
expire_days = max(
self.config.record.alerts.retain.days,
self.config.record.detections.retain.days,
self.config.record.effective_alert_days,
self.config.record.effective_detection_days,
)
file_extension = None # mp4 clips are no longer stored in /clips
update_params = {"has_clip": False}
@@ -278,15 +280,13 @@ class EventCleanup(threading.Thread):
## Expire events from cameras based on the camera config
for name, camera in self.config.cameras.items():
expire_days = max(
camera.record.alerts.retain.days,
camera.record.detections.retain.days,
)
# effective days cover the sub window, keeping tracked objects
# in Explore while sub recordings and review items still exist
alert_expire_date = (
now - datetime.timedelta(days=camera.record.alerts.retain.days)
now - datetime.timedelta(days=camera.record.effective_alert_days)
).timestamp()
detection_expire_date = (
now - datetime.timedelta(days=camera.record.detections.retain.days)
now - datetime.timedelta(days=camera.record.effective_detection_days)
).timestamp()
# grab all events after specific time
expired_events = (
+5 -8
View File
@@ -159,7 +159,8 @@ class EventProcessor(threading.Thread):
if width is None or height is None:
return
first_detector = list(self.config.detectors.values())[0]
camera_model = self.config.model_for_camera(camera)
camera_detector = self.config.devices_for_model(camera_model)[0].detector
start_time = event_data["start_time"]
end_time = (
@@ -229,13 +230,9 @@ class EventProcessor(threading.Thread):
Event.thumbnail: event_data.get("thumbnail"),
Event.has_clip: event_data["has_clip"],
Event.has_snapshot: event_data["has_snapshot"],
Event.model_hash: first_detector.model.model_hash
if first_detector.model
else None,
Event.model_type: first_detector.model.model_type
if first_detector.model
else None,
Event.detector_type: first_detector.type,
Event.model_hash: camera_model.model_hash,
Event.model_type: camera_model.model_type,
Event.detector_type: camera_detector,
Event.data: {
"box": box,
"region": region,
+66 -122
View File
@@ -262,6 +262,10 @@ def get_tool_definitions(
`attribute` parameter is exposed for filtering by their labels. When the
embeddings model only understands English (JinaV1), the `semantic_query`
description instructs the model to write the query in English.
Descriptions here stay mechanical: which tool to reach for, and how the
filters relate to each other, is stated once in the system prompt so the
guidance is not paid for twice on every request.
"""
search_objects_properties: dict[str, Any] = {
"camera": {
@@ -270,26 +274,13 @@ def get_tool_definitions(
},
"label": {
"type": "string",
"description": (
"Generic object class to filter by — one of the tracked detector "
"labels such as 'person', 'package', 'car', 'dog', 'bird'. Use "
"this for broad queries like 'show me all cars today'. Combine "
"with semantic_query when the user also describes appearance or "
"behavior (e.g. label='person', semantic_query='riding a lawn "
"mower')."
),
"description": "Tracked object class to filter by.",
},
"sub_label": {
"type": "string",
"description": (
"Filter by a DISCRETE NAMED entity recognized in the detection. "
"Use this for: a known person's name ('John'), a delivery "
"company ('Amazon', 'UPS'), a recognized animal species or "
"breed ('blue jay', 'cardinal', 'golden retriever'), or a "
"license plate string. When filtering by a specific name, set "
"only sub_label and leave label unset. Do NOT use sub_label "
"for descriptions of appearance, clothing, or actions — those "
"belong in semantic_query."
"Name recognized in the detection: a person, delivery company, "
"animal species or breed, or license plate."
),
},
"after": {
@@ -313,20 +304,11 @@ def get_tool_definitions(
}
if attribute_classifications:
model_outline = "; ".join(
f"{m['name']} (applies to {', '.join(m['objects']) or 'any object'})"
for m in attribute_classifications
)
search_objects_properties["attribute"] = {
"type": "string",
"description": (
"Filter by a classification attribute label produced by a "
"configured attribute classification model. Use this INSTEAD "
"of semantic_query when the user's request matches one of "
"these classifications. Configured models: "
f"{model_outline}. "
"Set the value to the attribute label that matches the user's "
"phrasing (case-sensitive)."
"Attribute label produced by a configured classification model "
"(case-sensitive)."
),
}
@@ -334,29 +316,12 @@ def get_tool_definitions(
search_objects_properties["semantic_query"] = {
"type": "string",
"description": (
"Optional natural-language description of a PHYSICAL "
"CHARACTERISTIC, APPEARANCE, or ACTIVITY the user mentioned, "
"used to semantically narrow results. Only set this when the "
"user describes something beyond what label and sub_label can "
"express on their own.\n"
"USE for descriptive phrases like: 'riding a lawn mower', "
"'wearing a red jacket', 'carrying a package', 'walking a "
"dog', 'on a bicycle', 'holding an umbrella'.\n"
"DO NOT USE for:\n"
"- specific named people, pets, or delivery companies → use sub_label\n"
"- animal species or breed names like 'blue jay', 'cardinal', "
"'golden retriever' → use sub_label\n"
"- license plate strings → use sub_label\n"
"- generic object queries like 'all cars today' or 'every "
"person' → use label alone with no semantic_query\n"
"When set, combine with label/time/camera/zone filters as "
"usual (e.g. label='person', semantic_query='riding a lawn "
"mower', after='2024-05-01T00:00:00Z')."
"Description of an appearance or activity, used to semantically "
"narrow results."
+ (
" The configured embeddings model only understands "
"English, so always write semantic_query in English, "
"translating the user's description if they phrased it "
"in another language."
" The configured embeddings model only understands English, so "
"always write this in English, translating the user's "
"description if they phrased it in another language."
if embeddings_language == "english"
else ""
)
@@ -364,26 +329,10 @@ def get_tool_definitions(
}
search_objects_description = (
"Search the historical record of detected objects in Frigate. "
"Use this ONLY for questions about the PAST — e.g. 'did anyone come by today?', "
"'when was the last car?', 'show me detections from yesterday'. "
"Do NOT use this for monitoring or alerting requests about future events — "
"use start_camera_watch instead for those. "
"An 'object' in Frigate represents a tracked detection (e.g., a person, package, car).\n\n"
"Choose filters based on what the user is asking for:\n"
"- Generic class query ('show me all cars today'): set `label` only.\n"
"- Specific NAMED entity (known person, delivery company, animal "
"species/breed like 'blue jay' or 'golden retriever', license "
"plate): set `sub_label` only and leave `label` unset.\n"
"Search the historical record of tracked detections. Use this ONLY for "
"questions about the PAST, e.g. 'did anyone come by today?', 'when was the "
"last car?'. For alerting on future events use start_camera_watch instead."
)
if semantic_search_enabled:
search_objects_description += (
"- Physical CHARACTERISTIC, APPEARANCE, or ACTIVITY that is not a "
"discrete name ('person riding a lawn mower', 'someone in a red "
"jacket', 'person carrying a package'): set `semantic_query` with "
"the descriptive phrase, optionally alongside `label` for the "
"object class. Do NOT put descriptive phrases in sub_label."
)
return [
{
@@ -398,20 +347,30 @@ def get_tool_definitions(
"required": [],
},
},
{
"type": "function",
"function": {
"name": "get_categorized_object_names",
"description": (
"Every name that can be attached as a sub_label, grouped by object "
"type: recognized faces, named license plates, classification "
"categories, and delivery logos. Takes no arguments and always "
"returns the complete map."
),
"parameters": {
"type": "object",
"properties": {},
"required": [],
},
},
},
{
"type": "function",
"function": {
"name": "find_similar_objects",
"description": (
"Find tracked objects that are visually and semantically similar "
"to a specific past event. Use this when the user references a "
"particular object they have seen and wants to find other "
"sightings of the same or similar one ('that green car', 'the "
"person in the red jacket', 'the package that was delivered'). "
"Prefer this over search_objects whenever the user's intent is "
"'find more like this specific one.' Use search_objects first "
"only if you need to locate the anchor event. Requires semantic "
"search to be enabled."
"Find tracked objects visually and semantically similar to a "
"specific past event. Requires semantic search to be enabled."
),
"parameters": {
"type": "object",
@@ -473,9 +432,8 @@ def get_tool_definitions(
"function": {
"name": "set_camera_state",
"description": (
"Change a camera's feature state (e.g., turn detection on/off, enable/disable recordings). "
"Use camera='*' to apply to all cameras at once. "
"Only call this tool when the user explicitly asks to change a camera setting. "
"Change a camera's feature state, e.g. turn detection on or off. "
"Only call this when the user explicitly asks to change a setting. "
"Requires admin privileges."
),
"parameters": {
@@ -495,7 +453,7 @@ def get_tool_definitions(
"motion",
"enabled",
"birdseye",
"birdseye_mode",
"birdseye_modes",
"improve_contrast",
"ptz_autotracker",
"motion_contour_area",
@@ -510,14 +468,14 @@ def get_tool_definitions(
],
"description": (
"The feature to change. Most features accept ON or OFF. "
"birdseye_mode accepts CONTINUOUS, MOTION, or OBJECTS. "
"birdseye_modes accepts CONTINUOUS, MOTION, ALL_OBJECTS, ALERTS, DETECTIONS, NONE, or a comma-separated combination. "
"motion_contour_area and motion_threshold accept a number. "
"profile accepts a profile name or 'none' to deactivate (requires camera='*')."
),
},
"value": {
"type": "string",
"description": "The value to set. ON or OFF for toggles, a number for thresholds, a profile name or 'none' for profile.",
"description": "The value to set, as accepted by the chosen feature.",
},
},
"required": ["camera", "feature", "value"],
@@ -529,11 +487,9 @@ def get_tool_definitions(
"function": {
"name": "get_live_context",
"description": (
"Get the current live image and detection information for a single camera: objects being tracked, "
"zones, timestamps. Use this to understand what is visible in the live view. "
"Call this when answering questions about what is happening right now on a specific camera. "
"Operates on one camera at a time; call the tool again for each additional camera. "
"Wildcards and empty values are not accepted."
"Current live image and detections (tracked objects, zones, "
"timestamps) for one camera. Use this for questions about what is "
"happening right now. Call it again for each additional camera."
),
"parameters": {
"type": "object",
@@ -541,8 +497,8 @@ def get_tool_definitions(
"camera": {
"type": "string",
"description": (
"Exact name of a single camera to get live context for. "
"Wildcards (e.g. '*', 'all') and empty strings are not accepted."
"Exact name of a single camera. Wildcards (e.g. '*', "
"'all') and empty strings are not accepted."
),
},
},
@@ -555,10 +511,9 @@ def get_tool_definitions(
"function": {
"name": "start_camera_watch",
"description": (
"Start a continuous VLM watch job that monitors a camera and sends a notification "
"when a specified condition is met. Use this when the user wants to be alerted about "
"a future event, e.g. 'tell me when guests arrive' or 'notify me when the package is picked up'. "
"Only one watch job can run at a time. Returns a job ID."
"Start a continuous watch job that monitors a camera and notifies "
"the user when a condition is met, e.g. 'tell me when guests "
"arrive'. Only one watch job can run at a time. Returns a job ID."
),
"parameters": {
"type": "object",
@@ -598,10 +553,7 @@ def get_tool_definitions(
"type": "function",
"function": {
"name": "stop_camera_watch",
"description": (
"Cancel the currently running VLM watch job. Use this when the user wants to "
"stop a previously started watch, e.g. 'stop watching the front door'."
),
"description": "Cancel the currently running watch job.",
"parameters": {
"type": "object",
"properties": {},
@@ -614,11 +566,9 @@ def get_tool_definitions(
"function": {
"name": "get_profile_status",
"description": (
"Get the current profile status including the active profile and "
"timestamps of when each profile was last activated. Use this to "
"determine time periods for recap requests — e.g. when the user asks "
"'what happened while I was away?', call this first to find the relevant "
"time window based on profile activation history."
"Get the active profile and when each profile was last activated. "
"Call this before get_recap to derive the time window for requests "
"like 'what happened while I was away?'."
),
"parameters": {
"type": "object",
@@ -632,11 +582,9 @@ def get_tool_definitions(
"function": {
"name": "get_recap",
"description": (
"Get a recap of all activity (alerts and detections) for a given time period. "
"Use this after calling get_profile_status to retrieve what happened during "
"a specific window — e.g. 'what happened while I was away?'. Returns a "
"chronological list of activity with camera, objects, zones, and GenAI-generated "
"descriptions when available. Summarize the results for the user."
"Get all activity (alerts and detections) for a time period, as a "
"chronological list with camera, objects, zones, and descriptions "
"when available. Summarize the results for the user."
),
"parameters": {
"type": "object",
@@ -723,14 +671,13 @@ def build_chat_system_prompt(
)
speed_units_section = f"\n\nReport object speeds to the user in {speed_unit}."
semantic_search_section = ""
filter_routing_section = (
"\n\nWhen routing a search_objects call, pick filters by the shape of the user's request:\n"
"- Generic class ('show me all cars today'): set `label` only.\n"
"- Specific named entity — a known person ('John'), delivery company ('Amazon'), animal species/breed ('blue jay', 'golden retriever'), or license plate: set `sub_label` only and leave `label` unset. Call get_categorized_object_names first and use the exact spelling it returns; a guessed spelling matches nothing. If the name is absent, say it is not configured rather than searching for it."
)
if semantic_search_enabled:
semantic_search_section = (
"\n\nWhen routing a search_objects call, pick filters by the shape of the user's request:\n"
"- Generic class ('show me all cars today'): set `label` only.\n"
"- Specific named entity — a known person ('John'), delivery company ('Amazon'), animal species/breed ('blue jay', 'cardinal', 'golden retriever'), or license plate: set `sub_label` only and leave `label` unset.\n"
"- Physical characteristic, appearance, or activity that is NOT a discrete name ('find me people riding a lawn mower', 'someone in a red jacket', 'a person carrying a package'): set `semantic_query` with the descriptive phrase, optionally combined with `label` for the object class. Never put descriptive phrases in `sub_label`."
)
filter_routing_section += "\n- Physical characteristic, appearance, or activity that is NOT a discrete name ('riding a lawn mower', 'someone in a red jacket'): set `semantic_query` with the descriptive phrase, optionally combined with `label`. Never put descriptive phrases in `sub_label`."
attribute_classification_section = ""
if attribute_classifications:
@@ -739,9 +686,9 @@ def build_chat_system_prompt(
for m in attribute_classifications
)
attribute_classification_section = (
"\n\nAttribute classification models are configured for the following object types:\n"
"\n\nConfigured attribute classification models:\n"
f"{model_lines}\n"
"When the user's request matches one of these classifications, set the search_objects `attribute` field to the matching label rather than using `semantic_query`. Reserve `semantic_query` for descriptive phrases that fall outside the configured attribute labels."
"When the user's request matches one of these classifications, set the search_objects `attribute` field to the matching label (case-sensitive) rather than using `semantic_query`. Reserve `semantic_query` for descriptive phrases outside the configured attribute labels."
)
return f"""You are a helpful assistant for Frigate, a security camera NVR system. You help users answer questions about their cameras, detected objects, and events.
@@ -750,9 +697,6 @@ Current server local date and time: {current_date_str} at {current_time_str}
Do not start your response with phrases like "I will check...", "Let me see...", or "Let me look...". Answer directly.
Always present times to the user in the server's local timezone. When tool results include start_time_local and end_time_local, use those exact strings when listing or describing detection times—do not convert or invent timestamps. Do not use UTC or ISO format with Z for the user-facing answer unless the tool result only provides Unix timestamps without local time fields.
When users ask about "today", "yesterday", "this week", etc., use the current date above as reference.
When searching for objects or events, use ISO 8601 format for dates (e.g., {current_date_str}T00:00:00Z for the start of today).
Always be accurate with time calculations based on the current date provided.
Always present times in the server's local timezone. When tool results include start_time_local and end_time_local, quote those strings exactly; never convert or invent timestamps, and fall back to UTC or ISO format only when a result has no local time fields. Resolve relative dates like "today" or "this week" against the current date above, and pass dates to tools in ISO 8601 (e.g. {current_date_str}T00:00:00Z for the start of today).
When a user refers to a specific object they have seen or describe with identifying details ("that green car", "the person in the red jacket", "a package left today"), prefer the find_similar_objects tool over search_objects. Use search_objects first only to locate the anchor event, then pass its id to find_similar_objects. For generic queries like "show me all cars today", keep using search_objects. If a user message begins with [attached_event:<id>], treat that event id as the anchor for any similarity or "tell me more" request in the same message and call find_similar_objects with that id.{semantic_search_section}{attribute_classification_section}{cameras_section}{speed_units_section}"""
When the user refers to a specific object they have seen ("that green car", "the person in the red jacket", "a package left today"), prefer find_similar_objects over search_objects, using search_objects only to locate the anchor event and passing its id along. Keep search_objects for generic queries like "show me all cars today". If a user message begins with [attached_event:<id>], treat that id as the anchor for any similarity or "tell me more" request in the same message.{filter_routing_section}{attribute_classification_section}{cameras_section}{speed_units_section}"""
+2 -1
View File
@@ -15,7 +15,7 @@ import numpy as np
from frigate.comms.inter_process import InterProcessRequestor
from frigate.config import FrigateConfig
from frigate.const import UPDATE_JOB_STATE
from frigate.const import STREAM_TYPE_MAIN, UPDATE_JOB_STATE
from frigate.jobs.job import Job
from frigate.jobs.manager import (
get_job_by_id,
@@ -485,6 +485,7 @@ class MotionSearchRunner(threading.Thread):
)
)
.where(Recordings.camera == camera_name)
.where(Recordings.stream_type == STREAM_TYPE_MAIN)
.order_by(Recordings.start_time.asc())
)
+2 -20
View File
@@ -17,6 +17,7 @@ import numpy as np
from frigate.config import CameraConfig
from frigate.ffmpeg_presets import parse_preset_hardware_acceleration_decode
from frigate.util.ffmpeg import terminate_ffmpeg_stream
from frigate.util.services import auto_detect_hwaccel
logger = logging.getLogger(__name__)
@@ -88,25 +89,6 @@ def _read_exact(stream: IO[bytes], size: int) -> bytes | None:
return bytes(buf)
def _terminate(proc: sp.Popen[bytes]) -> None:
"""Stop an ffmpeg decode process promptly."""
# Close the read end first so a blocked ffmpeg write unblocks (ffmpeg then
# sees a broken pipe), then signal it. The resulting ffmpeg write error is
# harmless and goes to the captured stderr.
if proc.stdout is not None:
try:
proc.stdout.close()
except OSError:
pass
if proc.poll() is None:
proc.terminate()
try:
proc.wait(timeout=5)
except sp.TimeoutExpired:
proc.kill()
proc.wait()
KEYFRAME_MAX_GAP_SECONDS = 2.0
@@ -222,7 +204,7 @@ def _run_vod_decode(
count += 1
yield frame
finally:
_terminate(proc)
terminate_ffmpeg_stream(proc)
stderr_file.close()
if count == 0 and software_retry and not should_stop():
+6
View File
@@ -79,6 +79,12 @@ class Recordings(Model):
segment_size = FloatField(default=0) # this should be stored as MB
regions = IntegerField(null=True)
motion_heatmap = JSONField(null=True) # 16x16 grid, 256 values (0-255)
keyframes = JSONField(null=True) # ms offsets; NULL = unprobed (legacy rows)
stream_type = CharField(default="main", max_length=8)
has_audio = BooleanField(null=True) # NULL = unknown (legacy rows)
audio_rate = IntegerField(null=True) # Hz; NULL = unknown (legacy rows)
audio_codec = CharField(null=True, max_length=20) # NULL = unknown (legacy rows)
video_codec = CharField(null=True, max_length=20) # NULL = unknown (legacy rows)
class ExportCase(Model):
+13 -1
View File
@@ -5,7 +5,19 @@ import threading
from numpy import ndarray
from frigate.detectors.detector_config import InputTensorEnum
from frigate.detectors.detector_config import InputTensorEnum, ModelConfig
def detection_frame_size(model: ModelConfig) -> int:
"""Get the shared memory size a camera needs to hand frames to a model.
Args:
model: The model the camera runs on
Returns:
Size in bytes of one model input frame
"""
return model.height * model.width * 3
class RequestStore:
+179 -130
View File
@@ -9,6 +9,7 @@ import queue
import subprocess as sp
import threading
import traceback
from dataclasses import dataclass
from multiprocessing.synchronize import Event as MpEvent
from typing import Any
@@ -16,9 +17,11 @@ import cv2
import numpy as np
from frigate.comms.inter_process import InterProcessRequestor
from frigate.comms.review_updater import ReviewDataSubscriber
from frigate.config import BirdseyeModeEnum, FfmpegConfig, FrigateConfig
from frigate.const import BASE_DIR, BIRDSEYE_PIPE, INSTALL_DIR, UPDATE_BIRDSEYE_LAYOUT
from frigate.output.ws_auth import ws_has_camera_access
from frigate.review.types import SeverityEnum
from frigate.util.image import (
SharedMemoryFrameManager,
copy_yuv_to_position,
@@ -28,6 +31,15 @@ from frigate.util.image import (
logger = logging.getLogger(__name__)
@dataclass(frozen=True, slots=True)
class BirdseyeActivity:
"""Activity signals used to decide whether a camera is shown in Birdseye."""
has_object: bool
has_motion: bool
severity: str | None
def get_standard_aspect_ratio(width: int, height: int) -> tuple[int, int]:
"""Ensure that only standard aspect ratios are used."""
# it is important that all ratios have the same scale
@@ -357,6 +369,7 @@ class BirdsEyeFrameManager:
settings.detect.height,
],
"last_active_frame": 0.0,
"live_active": False,
"current_frame": 0.0,
"layout_frame": 0.0,
"channel_dims": {
@@ -408,19 +421,33 @@ class BirdsEyeFrameManager:
channel_dims,
)
def camera_active(
self, mode: Any, object_box_count: int, motion_box_count: int
def camera_threshold_active(
self,
modes: list[BirdseyeModeEnum],
activity: BirdseyeActivity,
) -> bool:
if mode == BirdseyeModeEnum.continuous:
return True
"""Return whether activity subject to inactivity_threshold is present."""
return (BirdseyeModeEnum.motion in modes and activity.has_motion) or (
BirdseyeModeEnum.all_objects in modes and activity.has_object
)
if mode == BirdseyeModeEnum.motion and motion_box_count > 0:
return True
if mode == BirdseyeModeEnum.objects and object_box_count > 0:
return True
return False
def camera_live_active(
self,
modes: list[BirdseyeModeEnum],
activity: BirdseyeActivity,
) -> bool:
"""Return whether activity that ends the moment it stops is present."""
return (
BirdseyeModeEnum.continuous in modes
or (
BirdseyeModeEnum.alerts in modes
and activity.severity == SeverityEnum.alert
)
or (
BirdseyeModeEnum.detections in modes
and activity.severity == SeverityEnum.detection
)
)
def get_camera_coordinates(self) -> dict[str, dict[str, int]]:
"""Return the coordinates of each camera in the current layout."""
@@ -451,9 +478,15 @@ class BirdsEyeFrameManager:
and self.config.cameras[cam].birdseye.enabled
and self.config.cameras[cam].enabled_in_config
and self.config.cameras[cam].enabled
and cam_data["last_active_frame"] > 0
and cam_data["current_frame_time"] - cam_data["last_active_frame"]
< self.config.birdseye.inactivity_threshold
and (
cam_data["live_active"]
or (
cam_data["last_active_frame"] > 0
and cam_data["current_frame_time"]
- cam_data["last_active_frame"]
< self.config.birdseye.inactivity_threshold
)
)
]
)
logger.debug(f"Active cameras: {active_cameras}")
@@ -470,7 +503,9 @@ class BirdsEyeFrameManager:
limited_active_cameras = sorted(
active_cameras,
key=lambda active_camera: (
self.cameras[active_camera]["current_frame_time"]
0.0
if self.cameras[active_camera]["live_active"]
else self.cameras[active_camera]["current_frame_time"]
- self.cameras[active_camera]["last_active_frame"]
),
)
@@ -604,112 +639,92 @@ class BirdsEyeFrameManager:
) -> list[list[Any]] | None:
"""Calculate the optimal layout for 2+ cameras."""
def map_layout(
camera_layout: list[list[Any]], row_height: int
) -> tuple[int, int, list[list[Any]] | None]:
"""Map the calculated layout."""
candidate_layout = []
starting_x = 0
x = 0
max_width = 0
y = 0
def find_available_x(
current_x: int,
width: int,
reserved_ranges: list[tuple[int, int]],
max_width: int,
) -> int | None:
"""Find the first horizontal slot that does not collide with reservations."""
x = current_x
for row in camera_layout:
final_row = []
max_width = max(max_width, x)
x = starting_x
for cameras in row:
camera_dims = self.cameras[cameras[0]]["dimensions"].copy()
camera_aspect = cameras[1]
for reserved_start, reserved_end in sorted(reserved_ranges):
if x >= reserved_end:
continue
if camera_dims[1] > camera_dims[0]:
scaled_height = int(row_height * 2)
scaled_width = int(scaled_height * camera_aspect)
starting_x = scaled_width
else:
scaled_height = row_height
scaled_width = int(scaled_height * camera_aspect)
if x + width <= reserved_start:
return x
# layout is too large
if (
x + scaled_width > self.canvas.width
or y + scaled_height > self.canvas.height
):
return x + scaled_width, y + scaled_height, None
x = max(x, reserved_end)
final_row.append((cameras[0], (x, y, scaled_width, scaled_height)))
x += scaled_width
if x + width <= max_width:
return x
y += row_height
candidate_layout.append(final_row)
if max_width == 0:
max_width = x
return max_width, y, candidate_layout
canvas_aspect_x, canvas_aspect_y = self.canvas.get_aspect(coefficient)
camera_layout: list[list[Any]] = []
camera_layout.append([])
starting_x = 0
x = starting_x
y = 0
y_i = 0
max_y = 0
for camera in cameras_to_add:
camera_dims = self.cameras[camera]["dimensions"].copy()
camera_aspect_x, camera_aspect_y = self.canvas.get_camera_aspect(
camera, camera_dims[0], camera_dims[1]
)
if camera_dims[1] > camera_dims[0]:
portrait = True
else:
portrait = False
if (x + camera_aspect_x) <= canvas_aspect_x:
# insert if camera can fit on current row
camera_layout[y_i].append(
(
camera,
camera_aspect_x / camera_aspect_y,
)
)
if portrait:
starting_x = camera_aspect_x
else:
max_y = max(
max_y,
camera_aspect_y,
)
x += camera_aspect_x
else:
# move on to the next row and insert
y += max_y
y_i += 1
camera_layout.append([])
x = starting_x
if x + camera_aspect_x > canvas_aspect_x:
return None
camera_layout[y_i].append(
(
camera,
camera_aspect_x / camera_aspect_y,
)
)
x += camera_aspect_x
if y + max_y > canvas_aspect_y:
return None
row_height = int(self.canvas.height / coefficient)
total_width, total_height, standard_candidate_layout = map_layout(
camera_layout, row_height
)
def map_layout(row_height: int) -> tuple[int, int, list[list[Any]] | None]:
"""Lay out cameras row by row while reserving portrait spans for the next row."""
candidate_layout: list[list[Any]] = []
reserved_ranges: dict[int, list[tuple[int, int]]] = {}
current_row: list[Any] = []
row_index = 0
row_y = 0
row_x = 0
max_width = 0
max_height = 0
for camera in cameras_to_add:
camera_dims = self.cameras[camera]["dimensions"].copy()
camera_aspect_x, camera_aspect_y = self.canvas.get_camera_aspect(
camera, camera_dims[0], camera_dims[1]
)
portrait = camera_dims[1] > camera_dims[0]
scaled_height = row_height * 2 if portrait else row_height
scaled_width = int(scaled_height * (camera_aspect_x / camera_aspect_y))
while True:
x = find_available_x(
row_x,
scaled_width,
reserved_ranges.get(row_index, []),
self.canvas.width,
)
if x is not None and row_y + scaled_height <= self.canvas.height:
current_row.append(
(camera, (x, row_y, scaled_width, scaled_height))
)
row_x = x + scaled_width
max_width = max(max_width, row_x)
max_height = max(max_height, row_y + scaled_height)
if portrait:
reserved_ranges.setdefault(row_index + 1, []).append(
(x, row_x)
)
break
if current_row:
candidate_layout.append(current_row)
current_row = []
row_index += 1
row_y = row_index * row_height
row_x = 0
if row_y + scaled_height > self.canvas.height:
overflow_width = max(max_width, scaled_width)
overflow_height = row_y + scaled_height
return overflow_width, overflow_height, None
if current_row:
candidate_layout.append(current_row)
return max_width, max_height, candidate_layout
row_height = max(1, int(self.canvas.height / coefficient))
total_width, total_height, standard_candidate_layout = map_layout(row_height)
if not standard_candidate_layout:
# if standard layout didn't work
@@ -718,9 +733,9 @@ class BirdsEyeFrameManager:
total_width / self.canvas.width,
total_height / self.canvas.height,
)
row_height = int(row_height / scale_down_percent)
row_height = max(1, int(row_height / scale_down_percent))
total_width, total_height, standard_candidate_layout = map_layout(
camera_layout, row_height
row_height
)
if not standard_candidate_layout:
@@ -734,8 +749,8 @@ class BirdsEyeFrameManager:
1 / (total_width / self.canvas.width),
1 / (total_height / self.canvas.height),
)
row_height = int(row_height * scale_up_percent)
_, _, scaled_layout = map_layout(camera_layout, row_height)
row_height = max(1, int(row_height * scale_up_percent))
_, _, scaled_layout = map_layout(row_height)
if scaled_layout:
return scaled_layout
@@ -745,8 +760,7 @@ class BirdsEyeFrameManager:
def update(
self,
camera: str,
object_count: int,
motion_count: int,
activity: BirdseyeActivity,
frame_time: float,
frame: np.ndarray,
) -> tuple[bool, bool]:
@@ -760,22 +774,30 @@ class BirdsEyeFrameManager:
return False, False
force_update = False
camera_state = self.cameras.get(camera)
if camera_state is None:
return False, False
# disabling birdseye is a little tricky
if not camera_config.birdseye.enabled or not camera_config.enabled:
# if we've rendered a frame (we have a value for last_active_frame)
# then we need to set it to zero
if self.cameras[camera]["last_active_frame"] > 0:
self.cameras[camera]["last_active_frame"] = 0
# if we've rendered a frame (we have activity state) then clear it
if camera_state["last_active_frame"] > 0 or camera_state["live_active"]:
camera_state["last_active_frame"] = 0
camera_state["live_active"] = False
force_update = True
else:
return False, False
# update the last active frame for the camera
self.cameras[camera]["current_frame"] = frame.copy()
self.cameras[camera]["current_frame_time"] = frame_time
if self.camera_active(camera_config.birdseye.mode, object_count, motion_count):
self.cameras[camera]["last_active_frame"] = frame_time
camera_state["current_frame"] = frame.copy()
camera_state["current_frame_time"] = frame_time
modes = camera_config.birdseye.modes
if self.camera_threshold_active(modes, activity):
camera_state["last_active_frame"] = frame_time
camera_state["live_active"] = self.camera_live_active(modes, activity)
now = datetime.datetime.now().timestamp()
@@ -834,6 +856,8 @@ class Birdseye:
self.frame_manager = SharedMemoryFrameManager()
self.stop_event = stop_event
self.requestor = InterProcessRequestor()
self.review_subscriber = ReviewDataSubscriber("")
self.review_severity: dict[str, str] = {}
self.idle_fps: float = self.config.birdseye.idle_heartbeat_fps
self._idle_interval: float | None = (
(1.0 / self.idle_fps) if self.idle_fps > 0 else None
@@ -864,6 +888,21 @@ class Birdseye:
self.birdseye_manager.clear_frame()
self.__send_new_frame()
def check_review_updates(self) -> None:
"""Drain review updates so each camera's active severity stays current."""
while True:
update = self.review_subscriber.check_for_update(timeout=0)
if update is None:
break
camera = update["after"]["camera"]
if update["type"] == "end":
self.review_severity.pop(camera, None)
else:
self.review_severity[camera] = update["after"]["severity"]
def add_camera(self, camera: str) -> None:
"""Add a camera to the birdseye manager."""
self.birdseye_manager.add_camera(camera)
@@ -872,6 +911,7 @@ class Birdseye:
def remove_camera(self, camera: str) -> None:
"""Remove a camera from the birdseye manager."""
self.birdseye_manager.remove_camera(camera)
self.review_severity.pop(camera, None)
logger.debug(f"Removed camera {camera} from birdseye")
def write_data(
@@ -882,10 +922,18 @@ class Birdseye:
frame_time: float,
frame: np.ndarray,
) -> None:
activity = BirdseyeActivity(
has_object=any(
not tracked_object["false_positive"]
for tracked_object in current_tracked_objects
),
has_motion=bool(motion_boxes),
severity=self.review_severity.get(camera),
)
frame_changed, frame_layout_changed = self.birdseye_manager.update(
camera,
len([o for o in current_tracked_objects if not o["stationary"]]),
len(motion_boxes),
activity,
frame_time,
frame,
)
@@ -906,5 +954,6 @@ class Birdseye:
self.__send_new_frame()
def stop(self) -> None:
self.review_subscriber.stop()
self.converter.join()
self.broadcaster.join()
+17 -7
View File
@@ -51,8 +51,12 @@ def check_disabled_camera_update(
for camera, last_update in write_times.items():
offline_time = now - last_update
camera_config = config.cameras.get(camera)
if config.cameras[camera].enabled:
if camera_config is None:
continue
if camera_config.enabled:
has_enabled_camera = True
else:
# flag camera as offline when it is disabled
@@ -62,8 +66,8 @@ def check_disabled_camera_update(
# last camera update was more than 1 second ago
# need to send empty data to birdseye because current
# frame is now out of date
cam_width = config.cameras[camera].detect.width
cam_height = config.cameras[camera].detect.height
cam_width = camera_config.detect.width
cam_height = camera_config.detect.height
if cam_width is None or cam_height is None:
raise ValueError(f"Camera {camera} detect dimensions not configured")
@@ -184,6 +188,11 @@ class OutputProcess(FrigateProcess):
self.config.birdseye = birdseye_config
logger.debug("Applied dynamic birdseye config update")
# drain review updates every iteration, not just when birdseye is
# being consumed, so a dropped end never strands a camera
if birdseye is not None:
birdseye.check_review_updates()
# check if there is an updated config
updates = config_subscriber.check_for_updates()
@@ -309,10 +318,11 @@ class OutputProcess(FrigateProcess):
regions,
) = data
frame = frame_manager.get(
frame_name, self.config.cameras[camera].frame_shape_yuv
)
frame_manager.close(frame_name)
camera_config = self.config.cameras.get(camera)
if camera_config is not None:
frame_manager.get(frame_name, camera_config.frame_shape_yuv)
frame_manager.close(frame_name)
detection_subscriber.stop()
+21 -20
View File
@@ -799,14 +799,24 @@ class PtzAutoTracker:
except TimeoutError:
continue
# both are popped when the camera is deleted, so resolve them once
# here and use the locals for the rest of the move; a move already
# in flight then finishes against valid objects
metrics = self.ptz_metrics.get(camera)
camera_config = self.config.cameras.get(camera)
if metrics is None or camera_config is None:
logger.debug("%s: Dropping queued move, camera was removed", camera)
continue
async with self.move_queue_locks[camera]:
frame_time, pan, tilt, zoom = move_data
# if we're receiving move requests during a PTZ move, ignore them
if ptz_moving_at_frame_time(
frame_time,
self.ptz_metrics[camera].start_time.value,
self.ptz_metrics[camera].stop_time.value,
metrics.start_time.value,
metrics.stop_time.value,
):
logger.debug(
f"{camera}: Move queue: PTZ moving, dequeueing move request - frame time: {frame_time}, final pan: {pan}, final tilt: {tilt}, final zoom: {zoom}"
@@ -815,7 +825,7 @@ class PtzAutoTracker:
else:
if (
self.config.cameras[camera].onvif.autotracking.zooming
camera_config.onvif.autotracking.zooming
== ZoomingModeEnum.relative
):
await self.onvif._move_relative(camera, pan, tilt, zoom, 1)
@@ -824,25 +834,22 @@ class PtzAutoTracker:
await self.onvif._move_relative(camera, pan, tilt, 0, 1)
# Wait until the camera finishes moving
while not self.ptz_metrics[camera].motor_stopped.is_set():
while not metrics.motor_stopped.is_set():
await self.onvif.get_camera_status(camera)
if (
zoom > 0
and self.ptz_metrics[camera].zoom_level.value != zoom
):
if zoom > 0 and metrics.zoom_level.value != zoom:
await self.onvif._zoom_absolute(camera, zoom, 1)
# Wait until the camera finishes moving
while not self.ptz_metrics[camera].motor_stopped.is_set():
while not metrics.motor_stopped.is_set():
await self.onvif.get_camera_status(camera)
if self.config.cameras[camera].onvif.autotracking.movement_weights:
if camera_config.onvif.autotracking.movement_weights:
logger.debug(
f"{camera}: Predicted movement time: {self._predict_movement_time(camera, pan, tilt)}"
)
logger.debug(
f"{camera}: Actual movement time: {self.ptz_metrics[camera].stop_time.value - self.ptz_metrics[camera].start_time.value}"
f"{camera}: Actual movement time: {metrics.stop_time.value - metrics.start_time.value}"
)
# save metrics for better estimate calculations
@@ -851,21 +858,15 @@ class PtzAutoTracker:
and len(self.move_metrics[camera])
< AUTOTRACKING_MAX_MOVE_METRICS
and (pan != 0 or tilt != 0)
and self.config.cameras[
camera
].onvif.autotracking.calibrate_on_startup
and camera_config.onvif.autotracking.calibrate_on_startup
):
logger.debug(f"{camera}: Adding new values to move metrics")
self.move_metrics[camera].append(
{
"pan": pan,
"tilt": tilt,
"start_timestamp": self.ptz_metrics[
camera
].start_time.value,
"end_timestamp": self.ptz_metrics[
camera
].stop_time.value,
"start_timestamp": metrics.start_time.value,
"end_timestamp": metrics.stop_time.value,
}
)
+92 -56
View File
@@ -72,7 +72,11 @@ class OnvifController:
self.config_subscriber = CameraConfigUpdateSubscriber(
self.config,
self.config.cameras,
[CameraConfigUpdateEnum.onvif],
[
CameraConfigUpdateEnum.onvif,
CameraConfigUpdateEnum.add,
CameraConfigUpdateEnum.remove,
],
)
asyncio.run_coroutine_threadsafe(self._init_cameras(), self.loop)
@@ -101,6 +105,16 @@ class OnvifController:
if update_type == CameraConfigUpdateEnum.onvif.name:
for cam_name in cameras:
await self._reinit_camera(cam_name)
elif update_type == CameraConfigUpdateEnum.add.name:
# a camera added at runtime only needs ONVIF set up if
# it actually has an onvif host configured
for cam_name in cameras:
cam = self.config.cameras.get(cam_name)
if cam and cam.onvif.host:
await self._reinit_camera(cam_name)
elif update_type == CameraConfigUpdateEnum.remove.name:
for cam_name in cameras:
await self._remove_camera(cam_name)
except Exception:
logger.error("Error checking for ONVIF config updates")
@@ -113,6 +127,18 @@ class OnvifController:
except Exception:
logger.debug(f"Error closing ONVIF session for {cam_name}")
async def _remove_camera(self, cam_name: str) -> None:
"""Tear down the ONVIF session for a camera removed at runtime."""
if cam_name not in self.cams and cam_name not in self.camera_configs:
return
logger.debug(f"Tearing down ONVIF for {cam_name} after camera removal")
await self._close_camera(cam_name)
self.cams.pop(cam_name, None)
self.camera_configs.pop(cam_name, None)
self.failed_cams.pop(cam_name, None)
self.status_locks.pop(cam_name, None)
async def _reinit_camera(self, cam_name: str) -> None:
"""Re-initialize a camera after config change."""
logger.info(f"Re-initializing ONVIF for {cam_name} due to config change")
@@ -180,6 +206,11 @@ class OnvifController:
return False
async def _init_onvif(self, camera_name: str) -> bool:
camera_config = self.config.cameras.get(camera_name)
if camera_config is None:
return False
onvif: ONVIFCamera = self.cams[camera_name]["onvif"]
try:
await onvif.update_xaddrs()
@@ -235,7 +266,7 @@ class OnvifController:
p.token,
)
configured_profile = self.config.cameras[camera_name].onvif.profile
configured_profile = camera_config.onvif.profile
profile = None
if configured_profile is not None:
@@ -339,7 +370,7 @@ class OnvifController:
except (AttributeError, TypeError):
fov_space_id = None
autotracking_config = self.config.cameras[camera_name].onvif.autotracking
autotracking_config = camera_config.onvif.autotracking
autotracking_enabled = (
autotracking_config.enabled_in_config and autotracking_config.enabled
)
@@ -614,6 +645,11 @@ class OnvifController:
logger.error(f"{camera_name} does not support ONVIF RelativeMove (FOV).")
return
metrics = self.ptz_metrics.get(camera_name)
if metrics is None:
return
logger.debug(
f"{camera_name} called RelativeMove: pan: {pan} tilt: {tilt} zoom: {zoom}"
)
@@ -627,15 +663,11 @@ class OnvifController:
self.cams[camera_name]["active"] = True
# only track start_time for autotracking
if self.ptz_metrics[camera_name].autotracker_enabled.value:
self.ptz_metrics[camera_name].motor_stopped.clear()
logger.debug(
f"{camera_name}: PTZ start time: {self.ptz_metrics[camera_name].frame_time.value}"
)
self.ptz_metrics[camera_name].start_time.value = self.ptz_metrics[
camera_name
].frame_time.value
self.ptz_metrics[camera_name].stop_time.value = 0
if metrics.autotracker_enabled.value:
metrics.motor_stopped.clear()
logger.debug(f"{camera_name}: PTZ start time: {metrics.frame_time.value}")
metrics.start_time.value = metrics.frame_time.value
metrics.stop_time.value = 0
move_request = self.cams[camera_name]["relative_move_request"]
@@ -697,9 +729,14 @@ class OnvifController:
logger.error(f"{preset} is not a valid preset for {camera_name}")
return
metrics = self.ptz_metrics.get(camera_name)
if metrics is None:
return
self.cams[camera_name]["active"] = True
self.ptz_metrics[camera_name].start_time.value = 0
self.ptz_metrics[camera_name].stop_time.value = 0
metrics.start_time.value = 0
metrics.stop_time.value = 0
move_request = self.cams[camera_name]["move_request"]
preset_token = self.cams[camera_name]["presets"][preset]
@@ -738,6 +775,11 @@ class OnvifController:
logger.error(f"{camera_name} does not support ONVIF AbsoluteMove zooming.")
return
metrics = self.ptz_metrics.get(camera_name)
if metrics is None:
return
logger.debug(f"{camera_name} called AbsoluteMove: zoom: {zoom}")
if self.cams[camera_name]["active"]:
@@ -747,14 +789,10 @@ class OnvifController:
return
self.cams[camera_name]["active"] = True
self.ptz_metrics[camera_name].motor_stopped.clear()
logger.debug(
f"{camera_name}: PTZ start time: {self.ptz_metrics[camera_name].frame_time.value}"
)
self.ptz_metrics[camera_name].start_time.value = self.ptz_metrics[
camera_name
].frame_time.value
self.ptz_metrics[camera_name].stop_time.value = 0
metrics.motor_stopped.clear()
logger.debug(f"{camera_name}: PTZ start time: {metrics.frame_time.value}")
metrics.start_time.value = metrics.frame_time.value
metrics.stop_time.value = 0
move_request = self.cams[camera_name]["absolute_move_request"]
# function takes in 0 to 1 for zoom, interpolate to the values of the camera.
@@ -875,16 +913,18 @@ class OnvifController:
Returns camera details including features and presets if available.
"""
if not self.config.cameras[camera_name].enabled:
camera_config = self.config.cameras.get(camera_name)
if camera_config is None:
return {}
if not camera_config.enabled:
logger.debug(
f"Camera {camera_name} disabled, won't try to initialize ONVIF"
)
return {}
if camera_name not in self.cams.keys() and (
camera_name not in self.config.cameras
or not self.config.cameras[camera_name].onvif.host
):
if camera_name not in self.cams.keys() and (not camera_config.onvif.host):
logger.debug(f"ONVIF is not configured for {camera_name}")
return {}
@@ -985,6 +1025,12 @@ class OnvifController:
logger.error(f"ONVIF is not configured for {camera_name}")
return
metrics = self.ptz_metrics.get(camera_name)
camera_config = self.config.cameras.get(camera_name)
if metrics is None or camera_config is None:
return
if not self.cams[camera_name]["init"]:
if not await self._init_onvif(camera_name):
return
@@ -1023,36 +1069,29 @@ class OnvifController:
zoom_status is None or zoom_status == "IDLE"
):
self.cams[camera_name]["active"] = False
if not self.ptz_metrics[camera_name].motor_stopped.is_set():
self.ptz_metrics[camera_name].motor_stopped.set()
if not metrics.motor_stopped.is_set():
metrics.motor_stopped.set()
logger.debug(
f"{camera_name}: PTZ stop time: {self.ptz_metrics[camera_name].frame_time.value}"
f"{camera_name}: PTZ stop time: {metrics.frame_time.value}"
)
self.ptz_metrics[camera_name].stop_time.value = self.ptz_metrics[
camera_name
].frame_time.value
metrics.stop_time.value = metrics.frame_time.value
else:
self.cams[camera_name]["active"] = True
if self.ptz_metrics[camera_name].motor_stopped.is_set():
self.ptz_metrics[camera_name].motor_stopped.clear()
if metrics.motor_stopped.is_set():
metrics.motor_stopped.clear()
logger.debug(
f"{camera_name}: PTZ start time: {self.ptz_metrics[camera_name].frame_time.value}"
f"{camera_name}: PTZ start time: {metrics.frame_time.value}"
)
self.ptz_metrics[camera_name].start_time.value = self.ptz_metrics[
camera_name
].frame_time.value
self.ptz_metrics[camera_name].stop_time.value = 0
metrics.start_time.value = metrics.frame_time.value
metrics.stop_time.value = 0
if (
self.config.cameras[camera_name].onvif.autotracking.zooming
!= ZoomingModeEnum.disabled
):
if camera_config.onvif.autotracking.zooming != ZoomingModeEnum.disabled:
# store absolute zoom level as 0 to 1 interpolated from the values of the camera
self.ptz_metrics[camera_name].zoom_level.value = numpy.interp(
metrics.zoom_level.value = numpy.interp(
round(status.Position.Zoom.x, 2),
[
self.cams[camera_name]["absolute_zoom_range"]["XRange"]["Min"],
@@ -1061,25 +1100,22 @@ class OnvifController:
[0, 1],
)
logger.debug(
f"{camera_name}: Camera zoom level: {self.ptz_metrics[camera_name].zoom_level.value}"
f"{camera_name}: Camera zoom level: {metrics.zoom_level.value}"
)
# some hikvision cams won't update MoveStatus, so warn if it hasn't changed
if (
not self.ptz_metrics[camera_name].motor_stopped.is_set()
and not self.ptz_metrics[camera_name].reset.is_set()
and self.ptz_metrics[camera_name].start_time.value != 0
and self.ptz_metrics[camera_name].frame_time.value
> (self.ptz_metrics[camera_name].start_time.value + 10)
and self.ptz_metrics[camera_name].stop_time.value == 0
not metrics.motor_stopped.is_set()
and not metrics.reset.is_set()
and metrics.start_time.value != 0
and metrics.frame_time.value > (metrics.start_time.value + 10)
and metrics.stop_time.value == 0
):
logger.debug(
f"Start time: {self.ptz_metrics[camera_name].start_time.value}, Stop time: {self.ptz_metrics[camera_name].stop_time.value}, Frame time: {self.ptz_metrics[camera_name].frame_time.value}"
f"Start time: {metrics.start_time.value}, Stop time: {metrics.stop_time.value}, Frame time: {metrics.frame_time.value}"
)
# set the stop time so we don't come back into this again and spam the logs
self.ptz_metrics[camera_name].stop_time.value = self.ptz_metrics[
camera_name
].frame_time.value
metrics.stop_time.value = metrics.frame_time.value
logger.warning(
f"Camera {camera_name} is still in ONVIF 'MOVING' status."
)
+135 -30
View File
@@ -12,7 +12,14 @@ from typing import Any
from playhouse.sqlite_ext import SqliteExtDatabase
from frigate.config import CameraConfig, FrigateConfig, RetainModeEnum
from frigate.const import CACHE_DIR, CLIPS_DIR, MAX_WAL_SIZE, RECORD_DIR
from frigate.const import (
CACHE_DIR,
CLIPS_DIR,
MAX_WAL_SIZE,
RECORD_DIR,
STREAM_TYPE_MAIN,
STREAM_TYPE_SUB,
)
from frigate.models import Previews, Recordings, ReviewSegment, UserReviewStatus
from frigate.util.builtin import clear_and_unlink
from frigate.util.media import remove_empty_directories
@@ -20,6 +27,29 @@ from frigate.util.media import remove_empty_directories
logger = logging.getLogger(__name__)
def _filter_reviews_for_pass(
reviews: list[Any],
now: datetime.datetime,
alerts_days: float,
detections_days: float,
) -> list[Any]:
"""Limit reviews to those still within this pass's per-severity retention window.
Review rows survive to the longer of the main and sub retention windows,
so a pass that honored all of them would let extended sub retention keep
main recordings alive too. Filtering preserves sort order for the overlap
loop in expire_existing_camera_recordings.
"""
alert_cutoff = (now - datetime.timedelta(days=alerts_days)).timestamp()
detection_cutoff = (now - datetime.timedelta(days=detections_days)).timestamp()
return [
r
for r in reviews
if r.end_time is None
or (r.end_time >= (alert_cutoff if r.severity == "alert" else detection_cutoff))
]
class RecordingCleanup(threading.Thread):
"""Cleanup existing recordings based on retention config."""
@@ -65,11 +95,14 @@ class RecordingCleanup(threading.Thread):
self, config: CameraConfig, now: datetime.datetime
) -> set[Path]:
"""Delete review segments that are expired"""
alert_expire_date = (
now - datetime.timedelta(days=config.record.alerts.retain.days)
).timestamp()
# review rows survive to the longer of the main and sub windows so
# they stay visible while either stream still has recordings
alert_days = config.record.effective_alert_days
detection_days = config.record.effective_detection_days
alert_expire_date = (now - datetime.timedelta(days=alert_days)).timestamp()
detection_expire_date = (
now - datetime.timedelta(days=config.record.detections.retain.days)
now - datetime.timedelta(days=detection_days)
).timestamp()
expired_reviews = (
ReviewSegment.select(ReviewSegment.id, ReviewSegment.thumb_path)
@@ -109,8 +142,11 @@ class RecordingCleanup(threading.Thread):
def expire_existing_camera_recordings(
self,
stream_type: str,
continuous_expire_date: float,
motion_expire_date: float,
alerts_retain_mode: RetainModeEnum,
detections_retain_mode: RetainModeEnum,
config: CameraConfig,
reviews: list[Any],
) -> set[Path]:
@@ -130,6 +166,11 @@ class RecordingCleanup(threading.Thread):
)
.where(
(Recordings.camera == config.name)
& (Recordings.stream_type == stream_type)
& (
Recordings.start_time
< max(continuous_expire_date, motion_expire_date)
)
& (
(
(Recordings.end_time < continuous_expire_date)
@@ -175,9 +216,9 @@ class RecordingCleanup(threading.Thread):
):
keep = True
mode = (
config.record.alerts.retain.mode
alerts_retain_mode
if review.severity == "alert"
else config.record.detections.retain.mode
else detections_retain_mode
)
break
@@ -216,6 +257,10 @@ class RecordingCleanup(threading.Thread):
Recordings.id << deleted_recordings_list[i : i + max_deletes]
).execute()
# previews follow main retention, so only the main pass expires them
if stream_type != STREAM_TYPE_MAIN:
return maybe_empty_dirs
previews = (
Previews.select(
Previews.id,
@@ -292,27 +337,45 @@ class RecordingCleanup(threading.Thread):
expire_before = (
datetime.datetime.now() - datetime.timedelta(days=expire_days)
).timestamp()
no_camera_recordings = (
Recordings.select(
Recordings.id,
Recordings.path,
)
.where(
Recordings.camera.not_in(list(self.config.cameras.keys())), # type: ignore[call-arg, arg-type, misc]
Recordings.end_time < expire_before,
)
.namedtuples()
.iterator()
)
# enumerate the distinct cameras with one index seek each
db_cameras: list[str] = []
last_camera: str | None = None
while True:
query = Recordings.select(Recordings.camera)
if last_camera is not None:
query = query.where(Recordings.camera > last_camera)
next_camera = query.order_by(Recordings.camera.asc()).limit(1).scalar()
if next_camera is None:
break
db_cameras.append(next_camera)
last_camera = next_camera
maybe_empty_dirs = set()
deleted_recordings = set()
for recording in no_camera_recordings:
recording_path = Path(recording.path)
recording_path.unlink(missing_ok=True)
deleted_recordings.add(recording.id)
maybe_empty_dirs.add(recording_path.parent)
for camera in db_cameras:
if camera in self.config.cameras:
continue
no_camera_recordings = (
Recordings.select(
Recordings.id,
Recordings.path,
)
.where(
Recordings.camera == camera,
Recordings.end_time < expire_before,
)
.namedtuples()
.iterator()
)
for recording in no_camera_recordings:
recording_path = Path(recording.path)
recording_path.unlink(missing_ok=True)
deleted_recordings.add(recording.id)
maybe_empty_dirs.add(recording_path.parent)
logger.debug(f"Expiring {len(deleted_recordings)} recordings")
# delete up to 100,000 at a time
@@ -342,6 +405,20 @@ class RecordingCleanup(threading.Thread):
)
).timestamp()
# computed here so the reviews window below covers both passes
sub_continuous_expire_date = (
now - datetime.timedelta(days=config.record.sub.continuous.days)
).timestamp()
sub_motion_expire_date = (
now
- datetime.timedelta(
days=max(
config.record.sub.motion.days,
config.record.sub.continuous.days,
) # can't keep motion for less than continuous
)
).timestamp()
# Get all the reviews to check against
reviews = (
ReviewSegment.select(
@@ -351,18 +428,46 @@ class RecordingCleanup(threading.Thread):
)
.where(
ReviewSegment.camera == camera,
# candidate recordings can extend up to continuous_expire_date
# (the no-motion no-audio branch of the recordings query),
# so reviews must cover that full range to avoid deleting
# segments that overlap recent alerts/detections.
ReviewSegment.start_time < continuous_expire_date,
# candidate recordings reach the later of the two passes'
# continuous cutoffs, so reviews must cover that whole
# range or segments overlapping recent alerts get deleted
ReviewSegment.start_time
< max(continuous_expire_date, sub_continuous_expire_date),
)
.order_by(ReviewSegment.start_time)
.namedtuples()
)
maybe_empty_dirs |= self.expire_existing_camera_recordings(
continuous_expire_date, motion_expire_date, config, reviews
STREAM_TYPE_MAIN,
continuous_expire_date,
motion_expire_date,
config.record.alerts.retain.mode,
config.record.detections.retain.mode,
config,
_filter_reviews_for_pass(
reviews,
now,
config.record.alerts.retain.days,
config.record.detections.retain.days,
),
)
# runs even when sub recording is disabled so old rows still
# expire
maybe_empty_dirs |= self.expire_existing_camera_recordings(
STREAM_TYPE_SUB,
sub_continuous_expire_date,
sub_motion_expire_date,
config.record.sub.alerts.mode,
config.record.sub.detections.mode,
config,
_filter_reviews_for_pass(
reviews,
now,
config.record.sub.alerts.days,
config.record.sub.detections.days,
),
)
logger.debug(f"End camera: {camera}.")
+38 -30
View File
@@ -12,6 +12,7 @@ import threading
from collections.abc import Callable
from enum import Enum
from pathlib import Path
from typing import Any
import pytz # type: ignore[import-untyped]
from peewee import DoesNotExist
@@ -24,6 +25,8 @@ from frigate.const import (
EXPORT_DIR,
MAX_PLAYLIST_SECONDS,
PREVIEW_FRAME_TYPE,
STREAM_TYPE_MAIN,
STREAM_TYPE_SUB,
)
from frigate.ffmpeg_presets import (
EncodeTypeEnum,
@@ -283,6 +286,29 @@ class RecordingExporter(threading.Thread):
return input_duration * factor
def _get_recordings_for_range(self, stream_type: str) -> list[Any]:
"""Fetch one stream type's recording rows overlapping the export range."""
return list(
Recordings.select(
Recordings.start_time,
Recordings.end_time,
)
.where(
Recordings.start_time.between(self.start_time, self.end_time)
| Recordings.end_time.between(self.start_time, self.end_time)
| (
(self.start_time > Recordings.start_time)
& (self.end_time < Recordings.end_time)
)
)
.where(
(Recordings.camera == self.camera)
& (Recordings.stream_type == stream_type)
)
.order_by(Recordings.start_time.asc())
.iterator()
)
def _sum_source_duration_seconds(self) -> float | None:
"""Sum saved-video seconds inside [start_time, end_time].
@@ -293,19 +319,12 @@ class RecordingExporter(threading.Thread):
"""
try:
if self.playback_source == PlaybackSourceEnum.recordings:
rows = (
Recordings.select(Recordings.start_time, Recordings.end_time)
.where(
Recordings.start_time.between(self.start_time, self.end_time)
| Recordings.end_time.between(self.start_time, self.end_time)
| (
(self.start_time > Recordings.start_time)
& (self.end_time < Recordings.end_time)
)
)
.where(Recordings.camera == self.camera)
.iterator()
)
# never mix streams in one estimate; use main when available
# and fall back to sub for expired-main history
rows = self._get_recordings_for_range(STREAM_TYPE_MAIN)
if not rows:
rows = self._get_recordings_for_range(STREAM_TYPE_SUB)
else:
rows = (
Previews.select(Previews.start_time, Previews.end_time)
@@ -691,23 +710,12 @@ class RecordingExporter(threading.Thread):
if type(internal_port) is str:
internal_port = int(internal_port.split(":")[-1])
recordings = list(
Recordings.select(
Recordings.start_time,
Recordings.end_time,
)
.where(
Recordings.start_time.between(self.start_time, self.end_time)
| Recordings.end_time.between(self.start_time, self.end_time)
| (
(self.start_time > Recordings.start_time)
& (self.end_time < Recordings.end_time)
)
)
.where(Recordings.camera == self.camera)
.order_by(Recordings.start_time.asc())
.iterator()
)
# never mix streams in one playlist; use main when available and
# fall back to sub for expired-main history
recordings = self._get_recordings_for_range(STREAM_TYPE_MAIN)
if not recordings:
recordings = self._get_recordings_for_range(STREAM_TYPE_SUB)
playlist_lines: list[str] = []
if (self.end_time - self.start_time) <= MAX_PLAYLIST_SECONDS:
+342 -89
View File
@@ -15,6 +15,7 @@ from typing import Any
import numpy as np
import psutil
from peewee import fn
from frigate.comms.detections_updater import DetectionSubscriber, DetectionTypeEnum
from frigate.comms.inter_process import InterProcessRequestor
@@ -35,15 +36,48 @@ from frigate.const import (
MAX_SEGMENT_DURATION,
MAX_SEGMENTS_IN_CACHE,
RECORD_DIR,
STREAM_TYPE_MAIN,
STREAM_TYPE_SUB,
SUB_CACHE_TAG,
)
from frigate.models import Recordings, ReviewSegment
from frigate.review.types import SeverityEnum
from frigate.util.media import get_keyframe_offsets
from frigate.util.services import get_video_properties
logger = logging.getLogger(__name__)
STALE_RECORDINGS_INFO_TTL = MAX_SEGMENTS_IN_CACHE * MAX_SEGMENT_DURATION * 2
# cache filenames have whole-second resolution, so a contiguous segment's
# parsed start lands up to 1s before the previous segment's true end
SEGMENT_CHAIN_TOLERANCE_S = 1.0
# against an mtime-measured start, disagreement beyond this means
# accumulated probe-duration error and the chain re-anchors on the mtime
SEGMENT_CHAIN_DRIFT_LIMIT_S = 0.5
# probing every cached segment at once starves the camera and detection
# processes, and the probes then blow their own timeouts together, so
# segments get discarded as corrupt and the record watchdog restarts ffmpeg
MAX_CONCURRENT_SEGMENT_PROBES = 4
def parse_cache_segment_name(basename: str) -> tuple[str, str, str] | None:
"""Parse a cache segment basename into (camera, stream_type, date).
Main segments are named {camera}@{date}; sub segments {camera}@sub@{date}.
"""
try:
prefix, date = basename.rsplit("@", maxsplit=1)
except ValueError:
return None
if prefix.endswith(SUB_CACHE_TAG):
return (prefix[: -len(SUB_CACHE_TAG)], STREAM_TYPE_SUB, date)
return (prefix, STREAM_TYPE_MAIN, date)
class SegmentInfo:
def __init__(
@@ -83,6 +117,10 @@ class SegmentInfo:
class RecordingMaintainer(threading.Thread):
# move_files replaces this per cycle: an asyncio primitive binds to the
# first event loop that contends it, and every cycle runs in a new loop
probe_semaphore = asyncio.Semaphore(MAX_CONCURRENT_SEGMENT_PROBES)
def __init__(self, config: FrigateConfig, stop_event: MpEvent):
super().__init__(name="recording_maintainer")
self.config = config
@@ -100,10 +138,101 @@ class RecordingMaintainer(threading.Thread):
self.stop_event = stop_event
self.object_recordings_info: dict[str, list] = defaultdict(list)
self.audio_recordings_info: dict[str, list] = defaultdict(list)
self.end_time_cache: dict[str, tuple[datetime.datetime, float]] = {}
# cache_path -> (end_time, duration, has_audio, audio_rate,
# audio_codec, video_codec, keyframes)
self.end_time_cache: dict[
str,
tuple[
datetime.datetime,
float,
bool | None,
int | None,
str | None,
str | None,
list[int] | None,
],
] = {}
# last known capture end per (camera, stream_type); 0.0 marks a key
# whose DB seed found no rows
self.last_segment_end: dict[tuple[str, str], float] = {}
self.unexpected_cache_files_logged: bool = False
def _get_last_segment_end(self, camera: str, stream_type: str) -> float | None:
"""Return the last known capture end time for a camera stream.
Lazily seeds from the most recent stored recording so start-time
chains survive restarts.
"""
key = (camera, stream_type)
if key not in self.last_segment_end:
last_db_end = (
Recordings.select(fn.MAX(Recordings.end_time))
.where(
Recordings.camera == camera,
Recordings.stream_type == stream_type,
)
.scalar()
)
# the 0.0 sentinel keeps the seed query from repeating
self.last_segment_end[key] = last_db_end if last_db_end is not None else 0.0
return self.last_segment_end[key] or None
def _resolve_segment_start(
self,
camera: str,
stream_type: str,
filename_start: datetime.datetime,
duration: float,
cache_path: str,
) -> datetime.datetime:
"""Resolve a segment's true start time from its cache file.
Cache filenames carry whole-second resolution, so the parsed start
sits up to 1s early. The cache file's mtime is the wall clock when
ffmpeg rolled the segment, so mtime minus the probed duration
restores the fractional start. Contiguous segments still chain to
the previous segment's end so rows stay exactly adjacent.
"""
filename_ts = filename_start.timestamp()
measured: float | None = None
try:
mtime = os.path.getmtime(cache_path)
except OSError:
mtime = None
if mtime is not None:
candidate = mtime - duration
# media shorter than its wall span (a stalled stream, an early
# close) derives a start past the truncation window, where the
# floored filename start is safer
if 0 <= candidate - filename_ts < SEGMENT_CHAIN_TOLERANCE_S:
measured = candidate
last_end = self._get_last_segment_end(camera, stream_type)
if measured is not None:
if (
last_end is not None
and abs(last_end - measured) < SEGMENT_CHAIN_DRIFT_LIMIT_S
):
return datetime.datetime.fromtimestamp(last_end, tz=datetime.UTC)
return datetime.datetime.fromtimestamp(measured, tz=datetime.UTC)
# no usable mtime: capture is continuous within a run, so a
# filename start just before the previous end chains to that end
if (
last_end is not None
and 0 <= last_end - filename_ts < SEGMENT_CHAIN_TOLERANCE_S
):
return datetime.datetime.fromtimestamp(last_end, tz=datetime.UTC)
return filename_start
async def move_files(self) -> None:
self.probe_semaphore = asyncio.Semaphore(MAX_CONCURRENT_SEGMENT_PROBES)
cache_files = [
d
for d in os.listdir(CACHE_DIR)
@@ -117,13 +246,17 @@ class RecordingMaintainer(threading.Thread):
for cache in cache_files:
cache_path = os.path.join(CACHE_DIR, cache)
basename = os.path.splitext(cache)[0]
try:
camera, date = basename.rsplit("@", maxsplit=1)
except ValueError:
parsed = parse_cache_segment_name(basename)
if parsed is None:
if not self.unexpected_cache_files_logged:
logger.warning("Skipping unexpected files in cache")
self.unexpected_cache_files_logged = True
continue
camera, stream_type, date = parsed
# this topic feeds main-stream health/sync consumers only
if stream_type == STREAM_TYPE_SUB:
continue
start_time = datetime.datetime.strptime(
date, CACHE_SEGMENT_FORMAT
@@ -167,8 +300,10 @@ class RecordingMaintainer(threading.Thread):
except psutil.Error:
continue
# group recordings by camera (skip in-use for validation/moving)
grouped_recordings: defaultdict[str, list[dict[str, Any]]] = defaultdict(list)
# group recordings by camera and stream type (skip in-use for validation/moving)
grouped_recordings: defaultdict[tuple[str, str], list[dict[str, Any]]] = (
defaultdict(list)
)
for cache in cache_files:
# Skip files currently in use
if cache in files_in_use:
@@ -176,32 +311,35 @@ class RecordingMaintainer(threading.Thread):
cache_path = os.path.join(CACHE_DIR, cache)
basename = os.path.splitext(cache)[0]
try:
camera, date = basename.rsplit("@", maxsplit=1)
except ValueError:
parsed = parse_cache_segment_name(basename)
if parsed is None:
if not self.unexpected_cache_files_logged:
logger.warning("Skipping unexpected files in cache")
self.unexpected_cache_files_logged = True
continue
camera, stream_type, date = parsed
# important that start_time is utc because recordings are stored and compared in utc
start_time = datetime.datetime.strptime(
date, CACHE_SEGMENT_FORMAT
).astimezone(datetime.UTC)
grouped_recordings[camera].append(
grouped_recordings[(camera, stream_type)].append(
{
"cache_path": cache_path,
"start_time": start_time,
"stream_type": stream_type,
}
)
# delete all cached files past the most recent MAX_SEGMENTS_IN_CACHE
keep_count = MAX_SEGMENTS_IN_CACHE
for camera in grouped_recordings.keys():
for key in grouped_recordings.keys():
camera, stream_type = key
# sort based on start time
grouped_recordings[camera] = sorted(
grouped_recordings[camera], key=lambda s: s["start_time"]
grouped_recordings[key] = sorted(
grouped_recordings[key], key=lambda s: s["start_time"]
)
camera_info = self.object_recordings_info[camera]
@@ -216,7 +354,7 @@ class RecordingMaintainer(threading.Thread):
r["start_time"].timestamp()
< most_recently_processed_frame_time
),
grouped_recordings[camera],
grouped_recordings[key],
)
)
)
@@ -226,103 +364,133 @@ class RecordingMaintainer(threading.Thread):
logger.warning(
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..."
)
to_remove = grouped_recordings[camera][:-keep_count]
to_remove = grouped_recordings[key][:-keep_count]
for rec in to_remove:
cache_path = rec["cache_path"]
Path(cache_path).unlink(missing_ok=True)
self.end_time_cache.pop(cache_path, None)
grouped_recordings[camera] = grouped_recordings[camera][-keep_count:]
grouped_recordings[key] = grouped_recordings[key][-keep_count:]
# see if detection has failed and unprocessed segments need to be deleted
unprocessed_segment_count = (
len(grouped_recordings[camera]) - processed_segment_count
len(grouped_recordings[key]) - processed_segment_count
)
if unprocessed_segment_count > keep_count:
logger.warning(
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..."
)
to_remove = grouped_recordings[camera][:-keep_count]
to_remove = grouped_recordings[key][:-keep_count]
for rec in to_remove:
cache_path = rec["cache_path"]
Path(cache_path).unlink(missing_ok=True)
self.end_time_cache.pop(cache_path, None)
grouped_recordings[camera] = grouped_recordings[camera][-keep_count:]
grouped_recordings[key] = grouped_recordings[key][-keep_count:]
tasks = []
for camera, recordings in grouped_recordings.items():
# frame stats are shared per camera across stream types, so trimming
# to one stream's oldest cache would pop frames the other still needs
min_start_per_camera: dict[str, float] = {}
for key, recordings in grouped_recordings.items():
camera, _ = key
oldest_start = recordings[0]["start_time"].timestamp()
if (
camera not in min_start_per_camera
or oldest_start < min_start_per_camera[camera]
):
min_start_per_camera[camera] = oldest_start
for camera, min_start in min_start_per_camera.items():
# clear out all the object recording info for old frames
while (
len(self.object_recordings_info[camera]) > 0
and self.object_recordings_info[camera][0][0]
< recordings[0]["start_time"].timestamp()
and self.object_recordings_info[camera][0][0] < min_start
):
self.object_recordings_info[camera].pop(0)
# clear out all the audio recording info for old frames
while (
len(self.audio_recordings_info[camera]) > 0
and self.audio_recordings_info[camera][0][0]
< recordings[0]["start_time"].timestamp()
and self.audio_recordings_info[camera][0][0] < min_start
):
self.audio_recordings_info[camera].pop(0)
# get all reviews with the end time after the start of the oldest cache file
# or with end_time None
reviews = (
ReviewSegment.select(
ReviewSegment.start_time,
ReviewSegment.end_time,
ReviewSegment.severity,
ReviewSegment.data,
tasks = []
reviews_by_camera: dict[str, Any] = {}
for key, recordings in grouped_recordings.items():
camera, stream_type = key
# get all reviews with the end time after the start of the oldest
# cache file or with end_time None; shared across stream types
if camera not in reviews_by_camera:
reviews_by_camera[camera] = (
ReviewSegment.select(
ReviewSegment.start_time,
ReviewSegment.end_time,
ReviewSegment.severity,
ReviewSegment.data,
)
.where(
ReviewSegment.camera == camera,
(ReviewSegment.end_time == None)
| (ReviewSegment.end_time >= min_start_per_camera[camera]),
)
.order_by(ReviewSegment.start_time)
)
.where(
ReviewSegment.camera == camera,
(ReviewSegment.end_time == None)
| (
ReviewSegment.end_time
>= recordings[0]["start_time"].timestamp()
),
)
.order_by(ReviewSegment.start_time)
)
reviews = reviews_by_camera[camera]
tasks.extend(
[self.validate_and_move_segment(camera, reviews, r) for r in recordings]
)
# publish most recently available recording time and None if disabled
camera_cfg = self.config.cameras.get(camera)
self.recordings_publisher.publish(
(
camera,
recordings[0]["start_time"].timestamp()
if camera_cfg and camera_cfg.record.enabled
else None,
None,
),
RecordingsDataTypeEnum.saved.value,
)
if stream_type == STREAM_TYPE_MAIN:
camera_cfg = self.config.cameras.get(camera)
self.recordings_publisher.publish(
(
camera,
recordings[0]["start_time"].timestamp()
if camera_cfg and camera_cfg.record.enabled
else None,
None,
),
RecordingsDataTypeEnum.saved.value,
)
self._expire_stale_recordings_info(grouped_recordings)
recordings_to_insert: list[dict[str, Any] | None] = await asyncio.gather(*tasks)
# fire and forget recordings entries
self.requestor.send_data(
INSERT_MANY_RECORDINGS,
[r for r in recordings_to_insert if r is not None],
# one segment must not abort the cycle: an exception propagating out
# of gather would abandon the other segments' in-flight probes
results: list[dict[str, Any] | None | BaseException] = await asyncio.gather(
*tasks, return_exceptions=True
)
recordings_to_insert: list[dict[str, Any]] = []
for result in results:
if isinstance(result, BaseException):
logger.error(
"Failed to validate and move a recording segment", exc_info=result
)
continue
if result is not None:
recordings_to_insert.append(result)
# fire and forget recordings entries
self.requestor.send_data(INSERT_MANY_RECORDINGS, recordings_to_insert)
def _expire_stale_recordings_info(
self, grouped_recordings: defaultdict[str, list[dict[str, Any]]]
self, grouped_recordings: defaultdict[tuple[str, str], list[dict[str, Any]]]
) -> None:
expire_before = datetime.datetime.now().timestamp() - STALE_RECORDINGS_INFO_TTL
# a camera is still active when any of its streams cached segments
cameras_with_cache = {camera for camera, _ in grouped_recordings}
for recordings_info in (
self.object_recordings_info,
self.audio_recordings_info,
):
for camera in list(recordings_info.keys()):
if camera in grouped_recordings:
if camera in cameras_with_cache:
continue
info = recordings_info[camera]
while info and info[0][0] < expire_before:
@@ -337,64 +505,121 @@ class RecordingMaintainer(threading.Thread):
) -> dict[str, Any] | None:
cache_path: str = recording["cache_path"]
start_time: datetime.datetime = recording["start_time"]
stream_type: str = recording["stream_type"]
# Just delete files if camera removed or recordings are turned off
if (
camera not in self.config.cameras
or not self.config.cameras[camera].record.enabled
or (
stream_type == STREAM_TYPE_SUB
and not self.config.cameras[camera].record.sub.enabled
)
):
self.drop_segment(cache_path)
return None
if cache_path in self.end_time_cache:
end_time, duration = self.end_time_cache[cache_path]
(
end_time,
duration,
has_audio,
audio_rate,
audio_codec,
video_codec,
keyframes,
) = self.end_time_cache[cache_path]
# recover the resolved start rather than reusing the truncated
# filename timestamp
start_time = end_time - datetime.timedelta(seconds=duration)
else:
segment_info = await get_video_properties(
self.config.ffmpeg, cache_path, get_duration=True
)
async with self.probe_semaphore:
segment_info = await get_video_properties(
self.config.ffmpeg, cache_path, get_duration=True
)
if not segment_info.get("has_valid_video", False):
logger.warning(
f"Invalid or missing video stream in segment {cache_path}. Discarding."
)
self.recordings_publisher.publish(
(camera, start_time.timestamp(), cache_path),
RecordingsDataTypeEnum.invalid.value,
)
if stream_type == STREAM_TYPE_MAIN:
self.recordings_publisher.publish(
(camera, start_time.timestamp(), cache_path),
RecordingsDataTypeEnum.invalid.value,
)
self.drop_segment(cache_path)
return None
duration = float(segment_info.get("duration", -1))
has_audio = segment_info.get("has_audio")
audio_rate = segment_info.get("audio_rate")
audio_codec = segment_info.get("audio_codec")
video_codec = segment_info.get("video_codec")
# ensure duration is within expected length
if 0 < duration < MAX_SEGMENT_DURATION:
# playback snaps mid-file entry points against these offsets
# instead of probing files on demand
async with self.probe_semaphore:
keyframes = await get_keyframe_offsets(cache_path)
start_time = self._resolve_segment_start(
camera, stream_type, start_time, duration, cache_path
)
end_time = start_time + datetime.timedelta(seconds=duration)
self.end_time_cache[cache_path] = (end_time, duration)
self.end_time_cache[cache_path] = (
end_time,
duration,
has_audio,
audio_rate,
audio_codec,
video_codec,
keyframes,
)
# segments later discarded by retention still advance the
# chain for the next kept segment
self.last_segment_end[(camera, stream_type)] = end_time.timestamp()
else:
if duration == -1:
logger.warning(f"Failed to probe corrupt segment {cache_path}")
logger.warning(f"Discarding a corrupt recording segment: {cache_path}")
self.recordings_publisher.publish(
(camera, start_time.timestamp(), cache_path),
RecordingsDataTypeEnum.invalid.value,
)
if stream_type == STREAM_TYPE_MAIN:
self.recordings_publisher.publish(
(camera, start_time.timestamp(), cache_path),
RecordingsDataTypeEnum.invalid.value,
)
self.drop_segment(cache_path)
return None
# this segment has a valid duration and has video data, so publish an update
self.recordings_publisher.publish(
(camera, start_time.timestamp(), cache_path),
RecordingsDataTypeEnum.valid.value,
)
if stream_type == STREAM_TYPE_MAIN:
self.recordings_publisher.publish(
(camera, start_time.timestamp(), cache_path),
RecordingsDataTypeEnum.valid.value,
)
record_config = self.config.cameras[camera].record
# sub's alerts/detections carry the retain mode directly, unlike
# main's nested retain config
if stream_type == STREAM_TYPE_SUB:
continuous_days = record_config.sub.continuous.days
motion_days = record_config.sub.motion.days
alerts_retain_mode = record_config.sub.alerts.mode
detections_retain_mode = record_config.sub.detections.mode
else:
continuous_days = record_config.continuous.days
motion_days = record_config.motion.days
alerts_retain_mode = record_config.alerts.retain.mode
detections_retain_mode = record_config.detections.retain.mode
segment_stats: SegmentInfo | None = None
highest = None
if record_config.continuous.days > 0:
if continuous_days > 0:
highest = "continuous"
elif record_config.motion.days > 0:
elif motion_days > 0:
highest = "motion"
# if we have continuous or motion recording enabled
@@ -426,11 +651,17 @@ class RecordingMaintainer(threading.Thread):
if not segment_stats.should_discard_segment(record_mode):
return await self.move_segment(
camera,
stream_type,
start_time,
end_time,
duration,
cache_path,
segment_stats,
has_audio,
audio_rate,
audio_codec,
video_codec,
keyframes,
)
# we fell through the continuous / motion check, so we need to check the review items
@@ -459,9 +690,9 @@ class RecordingMaintainer(threading.Thread):
if overlaps:
record_mode = (
record_config.alerts.retain.mode
alerts_retain_mode
if review.severity == "alert"
else record_config.detections.retain.mode
else detections_retain_mode
)
if segment_stats is None:
@@ -471,11 +702,17 @@ class RecordingMaintainer(threading.Thread):
# move from cache to recordings immediately
return await self.move_segment(
camera,
stream_type,
start_time,
end_time,
duration,
cache_path,
segment_stats,
has_audio,
audio_rate,
audio_codec,
video_codec,
keyframes,
)
else:
self.drop_segment(cache_path)
@@ -614,17 +851,24 @@ class RecordingMaintainer(threading.Thread):
async def move_segment(
self,
camera: str,
stream_type: str,
start_time: datetime.datetime,
end_time: datetime.datetime,
duration: float,
cache_path: str,
segment_info: SegmentInfo,
has_audio: bool | None = None,
audio_rate: int | None = None,
audio_codec: str | None = None,
video_codec: str | None = None,
keyframes: list[int] | None = None,
) -> dict[str, Any] | None:
# directory will be in utc due to start_time being in utc
# sub segments get a tagged directory to avoid filename collisions
directory = os.path.join(
RECORD_DIR,
start_time.strftime("%Y-%m-%d/%H"),
camera,
camera if stream_type == STREAM_TYPE_MAIN else f"{camera}{SUB_CACHE_TAG}",
)
os.makedirs(directory, exist_ok=True)
@@ -684,6 +928,7 @@ class RecordingMaintainer(threading.Thread):
return {
Recordings.id.name: f"{start_time.timestamp()}-{rand_id}",
Recordings.camera.name: camera,
Recordings.stream_type.name: stream_type,
Recordings.path.name: file_path,
Recordings.start_time.name: start_time.timestamp(),
Recordings.end_time.name: end_time.timestamp(),
@@ -695,6 +940,11 @@ class RecordingMaintainer(threading.Thread):
Recordings.dBFS.name: segment_info.average_dBFS,
Recordings.segment_size.name: segment_size,
Recordings.motion_heatmap.name: segment_info.motion_heatmap,
Recordings.has_audio.name: has_audio,
Recordings.audio_rate.name: audio_rate,
Recordings.audio_codec.name: audio_codec,
Recordings.video_codec.name: video_codec,
Recordings.keyframes.name: keyframes,
}
except Exception as e:
logger.error(f"Unable to store recording segment {cache_path}")
@@ -745,7 +995,9 @@ class RecordingMaintainer(threading.Thread):
regions,
) = data
if self.config.cameras[camera].record.enabled:
camera_config = self.config.cameras.get(camera)
if camera_config is not None and camera_config.record.enabled:
self.object_recordings_info[camera].append(
(
frame_time,
@@ -762,7 +1014,9 @@ class RecordingMaintainer(threading.Thread):
audio_detections,
) = data
if self.config.cameras[camera].record.enabled:
camera_config = self.config.cameras.get(camera)
if camera_config is not None and camera_config.record.enabled:
self.audio_recordings_info[camera].append(
(
frame_time,
@@ -784,11 +1038,10 @@ class RecordingMaintainer(threading.Thread):
try:
asyncio.run(self.move_files())
except Exception as e:
logger.error(
except Exception:
logger.exception(
"Error occurred when attempting to maintain recording cache"
)
logger.error(e)
duration = datetime.datetime.now().timestamp() - run_start
wait_time = max(0, 5 - duration)
+11 -2
View File
@@ -418,6 +418,11 @@ class ReviewSegmentMaintainer(threading.Thread):
return None
def _handle_camera_removed(self, camera: str) -> None:
"""Close out a deleted camera's segment so a reused name cannot inherit it."""
self.forcibly_end_segment(camera)
self.indefinite_events.pop(camera, None)
def update_existing_segment(
self,
segment: PendingReviewSegment,
@@ -476,7 +481,7 @@ class ReviewSegmentMaintainer(threading.Thread):
if not object["sub_label"]:
segment.detections[object["id"]] = object["label"]
elif object["sub_label"][0] in self.config.model.all_attributes:
elif object["sub_label"][0] in self.config.all_attributes:
segment.detections[object["id"]] = object["sub_label"][0]
else:
segment.detections[object["id"]] = f"{object['label']}-verified"
@@ -614,7 +619,7 @@ class ReviewSegmentMaintainer(threading.Thread):
for object in activity.get_all_objects():
if not object["sub_label"]:
detections[object["id"]] = object["label"]
elif object["sub_label"][0] in self.config.model.all_attributes:
elif object["sub_label"][0] in self.config.all_attributes:
detections[object["id"]] = object["sub_label"][0]
else:
detections[object["id"]] = f"{object['label']}-verified"
@@ -666,6 +671,10 @@ class ReviewSegmentMaintainer(threading.Thread):
for camera in updated_topics["enabled"]:
self.forcibly_end_segment(camera)
if "remove" in updated_topics:
for camera in updated_topics["remove"]:
self._handle_camera_removed(camera)
result = self.detection_subscriber.check_for_update(timeout=1)
if not result:
+14 -13
View File
@@ -322,19 +322,20 @@ async def set_gpu_stats(
async def set_npu_usages(config: FrigateConfig, all_stats: dict[str, Any]) -> None:
stats: dict[str, dict] = {}
for detector in config.detectors.values():
if detector.type == "rknn":
# Rockchip NPU usage
rk_usage = get_rockchip_npu_stats()
stats["rockchip"] = rk_usage
elif detector.type == "openvino" and detector.device == "NPU":
# OpenVINO NPU usage
ov_usage = get_openvino_npu_stats()
stats["openvino"] = ov_usage
elif detector.type == "axengine":
# AXERA NPU usage
axcl_usage = get_axcl_npu_stats()
stats["axengine"] = axcl_usage
for model in config.models:
for device in config.devices_for_model(model):
if device.detector == "rknn":
# Rockchip NPU usage
rk_usage = get_rockchip_npu_stats()
stats["rockchip"] = rk_usage
elif device.detector == "openvino" and device.device == "NPU":
# OpenVINO NPU usage
ov_usage = get_openvino_npu_stats()
stats["openvino"] = ov_usage
elif device.detector == "axengine":
# AXERA NPU usage
axcl_usage = get_axcl_npu_stats()
stats["axengine"] = axcl_usage
if stats:
all_stats["npu_usages"] = stats
+176 -50
View File
@@ -6,10 +6,19 @@ import threading
from multiprocessing.synchronize import Event as MpEvent
from pathlib import Path
from peewee import SQL, fn
from peewee import SQL, Case, fn
from frigate.config import FrigateConfig
from frigate.const import RECORD_DIR, REPLAY_CAMERA_PREFIX
from frigate.config.camera.updater import (
CameraConfigUpdateEnum,
CameraConfigUpdateSubscriber,
)
from frigate.const import (
RECORD_DIR,
REPLAY_CAMERA_PREFIX,
STREAM_TYPE_MAIN,
STREAM_TYPE_SUB,
)
from frigate.models import Event, Recordings
from frigate.util.builtin import clear_and_unlink
@@ -19,6 +28,7 @@ bandwidth_equation = Recordings.segment_size / (
)
MAX_CALCULATED_BANDWIDTH = 10000 # 10Gb/hr
BANDWIDTH_SAMPLE_TARGET = 50
class StorageMaintainer(threading.Thread):
@@ -29,6 +39,96 @@ class StorageMaintainer(threading.Thread):
self.config = config
self.stop_event = stop_event
self.camera_storage_stats: dict[str, dict] = {}
self.config_subscriber = CameraConfigUpdateSubscriber(
self.config,
self.config.cameras,
[CameraConfigUpdateEnum.record],
)
def _recording_stream_types(self, camera: str) -> tuple[str, ...]:
"""Return the stream types the camera is currently recording."""
camera_config = self.config.cameras.get(camera)
if camera_config is None or not camera_config.record.enabled:
return ()
if camera_config.record.sub.enabled:
return (STREAM_TYPE_MAIN, STREAM_TYPE_SUB)
return (STREAM_TYPE_MAIN,)
def expected_hourly_bandwidth(self) -> float:
"""Return the MB/hr the cameras are expected to write.
Only the streams a camera currently records are counted, so toggling
recording or sub stream recording is reflected without waiting for the
existing segments of a stopped stream to expire.
"""
total = 0.0
for camera, stats in self.camera_storage_stats.items():
stream_bandwidths = stats.get("bandwidth_by_stream", {})
total += sum(
stream_bandwidths.get(stream_type, 0)
for stream_type in self._recording_stream_types(camera)
)
return round(total, 2)
def _recent_stream_bandwidth(
self, camera: str, stream_type: str, window: int
) -> float | None:
"""Average MB/s over a stream's most recent rows, or None if no sample.
Zero-size rows are excluded inside the projection, not the WHERE
clause: a segment_size predicate baits the planner into the
(camera, segment_size) index plus a full sort of the camera's
history instead of the time-ordered index.
"""
recent = (
Recordings.select(
Case(
None,
[(Recordings.segment_size > 0, bandwidth_equation)],
None,
).alias("bw")
)
.where(
Recordings.camera == camera,
Recordings.stream_type == stream_type,
)
.order_by(Recordings.start_time.desc())
.limit(window)
.alias("recent")
)
avg: float | None = Recordings.select(fn.AVG(SQL("bw"))).from_(recent).scalar()
return avg
def _stream_sample_count(self, camera: str, stream_type: str) -> int:
"""Count a stream's non-zero segments, stopping at the sample target."""
count: int = (
Recordings.select(Recordings.id)
.where(
Recordings.camera == camera,
Recordings.stream_type == stream_type,
Recordings.segment_size > 0,
)
.limit(BANDWIDTH_SAMPLE_TARGET)
.count()
)
return count
def _needs_refresh(self, camera: str) -> bool:
"""Return whether a stream the camera records still lacks samples.
Counted per stream rather than per camera: a stream that starts
recording later has no samples of its own yet, and a camera-wide count
would report it settled on the strength of another stream's history.
"""
return any(
self._stream_sample_count(camera, stream_type) < BANDWIDTH_SAMPLE_TARGET
for stream_type in self._recording_stream_types(camera)
)
def calculate_camera_bandwidth(self) -> None:
"""Calculate an average MB/hr for each camera."""
@@ -37,45 +137,45 @@ class StorageMaintainer(threading.Thread):
if camera.startswith(REPLAY_CAMERA_PREFIX):
continue
# cameras with < 50 segments should be refreshed to keep size accurate
# when few segments are available
if self.camera_storage_stats.get(camera, {}).get("needs_refresh", True):
self.camera_storage_stats[camera] = {
"needs_refresh": (
Recordings.select(fn.COUNT("*"))
.where(Recordings.camera == camera, Recordings.segment_size > 0)
.scalar()
< 50
)
if not self.camera_storage_stats.get(camera, {}).get("needs_refresh", True):
continue
# calculate MB/hr from the last 100 segments of each stream
# type and sum the rates; mixing streams would average small
# sub segments against large main segments and underestimate
# the true write rate
bandwidth_by_stream: dict[str, float] = {}
for stream_type in (STREAM_TYPE_MAIN, STREAM_TYPE_SUB):
avg_bw = self._recent_stream_bandwidth(camera, stream_type, 100)
if avg_bw is None:
# the recent window can be all zero-size ingest
# glitches; look further back before concluding
# the stream writes nothing
avg_bw = self._recent_stream_bandwidth(camera, stream_type, 1000)
if avg_bw is not None:
bandwidth_by_stream[stream_type] = round(avg_bw * 3600, 2)
bandwidth = round(sum(bandwidth_by_stream.values()), 2)
if bandwidth > MAX_CALCULATED_BANDWIDTH:
logger.warning(
f"{camera} has a bandwidth of {bandwidth} MB/hr which exceeds the expected maximum. This typically indicates an issue with the cameras recordings."
)
# scale each stream so the per stream values still sum to
# the clamped total the UI displays alongside them
scale = MAX_CALCULATED_BANDWIDTH / bandwidth
bandwidth_by_stream = {
stream_type: round(value * scale, 2)
for stream_type, value in bandwidth_by_stream.items()
}
bandwidth = MAX_CALCULATED_BANDWIDTH
# calculate MB/hr from last 100 segments
try:
# Subquery to get last 100 segments, then average their bandwidth
last_100 = (
Recordings.select(bandwidth_equation.alias("bw"))
.where(Recordings.camera == camera, Recordings.segment_size > 0)
.order_by(Recordings.start_time.desc())
.limit(100)
.alias("recent")
)
bandwidth = round(
Recordings.select(fn.AVG(SQL("bw"))).from_(last_100).scalar()
* 3600,
2,
)
if bandwidth > MAX_CALCULATED_BANDWIDTH:
logger.warning(
f"{camera} has a bandwidth of {bandwidth} MB/hr which exceeds the expected maximum. This typically indicates an issue with the cameras recordings."
)
bandwidth = MAX_CALCULATED_BANDWIDTH
except TypeError:
bandwidth = 0
self.camera_storage_stats[camera]["bandwidth"] = bandwidth
logger.debug(f"{camera} has a bandwidth of {bandwidth} MiB/hr.")
self.camera_storage_stats[camera] = {
"needs_refresh": self._needs_refresh(camera),
"bandwidth": bandwidth,
"bandwidth_by_stream": bandwidth_by_stream,
}
logger.debug(f"{camera} has a bandwidth of {bandwidth} MiB/hr.")
def calculate_camera_usages(self) -> dict[str, dict]:
"""Calculate the storage usage of each camera."""
@@ -86,20 +186,42 @@ class StorageMaintainer(threading.Thread):
if camera.startswith(REPLAY_CAMERA_PREFIX):
continue
camera_storage = (
Recordings.select(fn.SUM(Recordings.segment_size))
.where(Recordings.camera == camera, Recordings.segment_size != 0)
.scalar()
stream_usages = {
row["stream_type"]: row["usage"] or 0
for row in (
Recordings.select(
Recordings.stream_type,
fn.SUM(Recordings.segment_size).alias("usage"),
)
.where(Recordings.camera == camera, Recordings.segment_size != 0)
.group_by(Recordings.stream_type)
.dicts()
)
}
stream_bandwidths = self.camera_storage_stats.get(camera, {}).get(
"bandwidth_by_stream", {}
)
camera_key = (
getattr(self.config.cameras[camera], "friendly_name", None) or camera
)
usages[camera_key] = {
"usage": camera_storage,
"usage": sum(stream_usages.values()),
"bandwidth": self.camera_storage_stats.get(camera, {}).get(
"bandwidth", 0
),
# only streams with segments on disk are reported, so a camera
# keeps its sub entry until sub retention expires those segments.
# bandwidth is null rather than 0 when the cache holds no sample
# for the stream, since 0 would claim it writes nothing
"streams": {
stream_type: {
"usage": stream_usages[stream_type],
"bandwidth": stream_bandwidths.get(stream_type),
}
for stream_type in (STREAM_TYPE_MAIN, STREAM_TYPE_SUB)
if stream_usages.get(stream_type)
},
}
return usages
@@ -108,9 +230,7 @@ class StorageMaintainer(threading.Thread):
"""Return if storage needs cleanup."""
# currently runs cleanup if less than 1 hour of space is left
# disk_usage should not spin up disks
hourly_bandwidth = sum(
[b["bandwidth"] for b in self.camera_storage_stats.values()]
)
hourly_bandwidth = self.expected_hourly_bandwidth()
remaining_storage = round(shutil.disk_usage(RECORD_DIR).free / pow(2, 20), 1)
logger.debug(
f"Storage cleanup check: {hourly_bandwidth} hourly with remaining storage: {remaining_storage}."
@@ -121,9 +241,7 @@ class StorageMaintainer(threading.Thread):
"""Remove oldest hour of recordings."""
logger.debug("Starting storage cleanup.")
deleted_segments_size = 0
hourly_bandwidth = sum(
[b["bandwidth"] for b in self.camera_storage_stats.values()]
)
hourly_bandwidth = self.expected_hourly_bandwidth()
recordings = (
Recordings.select(
@@ -283,10 +401,17 @@ class StorageMaintainer(threading.Thread):
"""Check every 5 minutes if storage needs to be cleaned up."""
if self.config.safe_mode:
logger.info("Safe mode enabled, skipping storage maintenance")
self.config_subscriber.stop()
return
self.calculate_camera_bandwidth()
while not self.stop_event.wait(300):
updated_topics = self.config_subscriber.check_for_updates()
for camera in updated_topics.get(CameraConfigUpdateEnum.record.name, []):
if camera in self.camera_storage_stats:
self.camera_storage_stats[camera]["needs_refresh"] = True
if not self.camera_storage_stats or True in [
r["needs_refresh"] for r in self.camera_storage_stats.values()
]:
@@ -299,4 +424,5 @@ class StorageMaintainer(threading.Thread):
)
self.reduce_storage_consumption()
self.config_subscriber.stop()
logger.info("Exiting storage maintainer...")
@@ -0,0 +1,55 @@
"""Tests for the audio labels API."""
import unittest
from unittest.mock import patch
from frigate.models import Event
from frigate.test.http_api.base_http_test import AuthTestClient, BaseTestHttp
class TestHttpAudioLabels(BaseTestHttp):
def setUp(self):
super().setUp([Event])
def _labels(self, config: dict | None = None) -> dict[str, str]:
if config:
self.minimal_config.update(config)
app = self.create_app()
with patch(
"frigate.api.app.load_labels", return_value={0: "speech", 1: "bark"}
):
with AuthTestClient(app) as client:
response = client.get("/audio_labels")
self.assertEqual(response.status_code, 200)
return response.json()
def test_the_default_labels_are_returned(self):
self.assertEqual(self._labels(), {"0": "speech", "1": "bark"})
def test_a_global_labelmap_override_is_offered(self):
# grouping several classes under one label makes that label selectable
labels = self._labels({"audio": {"labelmap": {0: "noise", 1: "noise"}}})
self.assertEqual(set(labels.values()), {"noise"})
def test_a_camera_labelmap_override_is_offered(self):
labels = self._labels(
{
"cameras": {
"front_door": {
**self.minimal_config["cameras"]["front_door"],
"audio": {"labelmap": {1: "dogs"}},
}
}
}
)
self.assertEqual(labels["1"], "dogs")
self.assertEqual(labels["0"], "speech")
if __name__ == "__main__":
unittest.main(verbosity=2)
@@ -390,7 +390,7 @@ class TestGo2rtcStreamAccess(BaseTestHttp):
intent and forward the request to go2rtc instead of short-circuiting with 400."""
app = self._make_app(_MULTI_CAMERA_CONFIG)
mock_response = type("R", (), {"ok": True, "status_code": 200, "text": "ok"})()
with patch.dict(os.environ, {"GO2RTC_ALLOW_ARBITRARY_EXEC": "true"}):
with patch("frigate.util.services._GO2RTC_ARBITRARY_EXEC_ENV", "true"):
with patch(
"frigate.api.camera.requests.put", return_value=mock_response
) as mock_put:
@@ -403,6 +403,20 @@ class TestGo2rtcStreamAccess(BaseTestHttp):
forwarded_src = mock_put.call_args.kwargs["params"]["src"]
assert forwarded_src == "exec:/tmp/something"
def test_add_stream_ignores_override_written_after_import(self):
"""The override is read once at import. A value written into os.environ
later, which is what the config's environment_vars block does, must not
unlock restricted sources."""
app = self._make_app(_MULTI_CAMERA_CONFIG)
with patch.dict(os.environ, {"GO2RTC_ALLOW_ARBITRARY_EXEC": "true"}):
with patch("frigate.api.camera.requests.put") as mock_put:
with AuthTestClient(app) as client:
resp = client.put("/go2rtc/streams/legit?src=exec:/tmp/something")
# A live go2rtc would also answer 400, so assert on the forward.
mock_put.assert_not_called()
assert resp.status_code == 400
assert resp.json().get("success") is False
def test_stream_alias_blocked_when_owning_camera_disallowed(self):
"""limited_user cannot access a stream alias that belongs to a camera they
are not allowed to see."""
@@ -440,3 +454,68 @@ class TestGo2rtcStreamAccess(BaseTestHttp):
f"limited_user should be denied on alias back_door_main; "
f"got {resp.status_code}"
)
class TestReviewSummaryAccess(BaseTestHttp):
"""Tests for POST /review/summarize/start/{start_ts}/end/{end_ts}.
The summary correlates each flagged event with overlapping activity on
other cameras, so it is gated on full camera access rather than scoped to
the caller's cameras. These tests pin that decision so the dependency is
not loosened without first scoping the query.
GenAI is not configured in unit tests, so an authorized request returns 400
while an unauthorized one is rejected with 403 before the handler runs.
"""
def setUp(self):
super().setUp([Event, ReviewSegment, Recordings])
self.minimal_config = _MULTI_CAMERA_CONFIG
self.app = super().create_app()
def tearDown(self):
self.app.dependency_overrides.clear()
super().tearDown()
def _summarize(self, allowed_cameras: list[str]):
async def mock_cameras(request: Request):
return allowed_cameras
self.app.dependency_overrides[get_allowed_cameras_for_filter] = mock_cameras
with AuthTestClient(self.app) as client:
return client.post("/review/summarize/start/0/end/9999999999")
def _assert_allowed(self, resp):
assert resp.status_code not in (401, 403), (
f"Caller should not be blocked; got {resp.status_code}"
)
def test_partial_camera_access_blocked(self):
assert self._summarize(["front_door"]).status_code == 403
def test_no_camera_access_blocked(self):
assert self._summarize([]).status_code == 403
def test_full_camera_access_allowed(self):
# Covers admin and viewer, which always resolve to every camera, and a
# custom role whose list happens to name them all.
self._assert_allowed(self._summarize(["front_door", "back_door"]))
def _summarize_as_role(self, role: str):
"""Summarize using the real role to allowed-cameras resolution."""
self.app.dependency_overrides.pop(get_allowed_cameras_for_filter, None)
with AuthTestClient(self.app) as client:
return client.post(
"/review/summarize/start/0/end/9999999999",
headers={"remote-user": "test", "remote-role": role},
)
def test_viewer_role_allowed(self):
# viewer is never camera restricted, so it resolves to every camera.
self._assert_allowed(self._summarize_as_role("viewer"))
def test_admin_role_allowed(self):
self._assert_allowed(self._summarize_as_role("admin"))
def test_restricted_role_blocked(self):
assert self._summarize_as_role("limited_user").status_code == 403
+16 -9
View File
@@ -7,7 +7,7 @@ from unittest.mock import MagicMock, Mock, patch
import ruamel.yaml
from frigate.config import FrigateConfig
from frigate.config import BirdseyeModeEnum, FrigateConfig
from frigate.config.camera.updater import (
CameraConfigUpdateEnum,
CameraConfigUpdatePublisher,
@@ -383,12 +383,15 @@ class TestConfigSetWildcardPropagation(BaseTestHttp):
Global birdseye only seeds enabled and mode; the camera copies are what
the output process actually reads. Sending just the global object makes
a worker guess which cameras were inheriting, and the only available
guess (mode still equals the previous global) wrongly claims a camera
whose explicit yaml mode happens to match.
guess (modes still equals the previous global) wrongly claims a camera
whose explicit yaml modes happens to match.
"""
self.minimal_config["birdseye"] = {"enabled": True, "mode": "motion"}
self.minimal_config["birdseye"] = {
"enabled": True,
"modes": ["motion"],
}
# explicit override that matches the global value being replaced
self.minimal_config["cameras"]["front_door"]["birdseye"] = {"mode": "motion"}
self.minimal_config["cameras"]["front_door"]["birdseye"] = {"modes": ["motion"]}
config_path = self._write_config_file()
mock_find_config.return_value = config_path
@@ -399,7 +402,7 @@ class TestConfigSetWildcardPropagation(BaseTestHttp):
resp = client.put(
"/config/set",
json={
"config_data": {"birdseye": {"mode": "continuous"}},
"config_data": {"birdseye": {"modes": ["continuous"]}},
"update_topic": "config/birdseye",
"requires_restart": 0,
},
@@ -411,7 +414,7 @@ class TestConfigSetWildcardPropagation(BaseTestHttp):
mock_publisher.publisher.publish.assert_called_once()
topic, settings = mock_publisher.publisher.publish.call_args[0]
self.assertEqual(topic, "config/birdseye")
self.assertEqual(settings.mode.value, "continuous")
self.assertEqual(settings.modes, [BirdseyeModeEnum.continuous])
published = {
call[0][0].camera: call[0][1]
@@ -425,8 +428,12 @@ class TestConfigSetWildcardPropagation(BaseTestHttp):
)
# the override survives, the inheriting camera follows global
self.assertEqual(published["front_door"].mode.value, "motion")
self.assertEqual(published["back_yard"].mode.value, "continuous")
self.assertEqual(
published["front_door"].modes, [BirdseyeModeEnum.motion]
)
self.assertEqual(
published["back_yard"].modes, [BirdseyeModeEnum.continuous]
)
finally:
os.unlink(config_path)
File diff suppressed because it is too large Load Diff
+113
View File
@@ -0,0 +1,113 @@
"""Tests for password change authorization."""
from fastapi import Request
from frigate.api.auth import get_current_user, hash_password, verify_password
from frigate.models import Event, Recordings, ReviewSegment, User
from frigate.test.http_api.base_http_test import AuthTestClient, BaseTestHttp
# Config carrying a custom role, which is the class of user the literal
# "viewer" check used to let through.
_CUSTOM_ROLE_CONFIG = {
"mqtt": {"host": "mqtt"},
"auth": {"roles": {"neighbor": ["front_door"]}, "hash_iterations": 10},
"cameras": {
"front_door": {
"ffmpeg": {
"inputs": [{"path": "rtsp://10.0.0.1:554/video", "roles": ["detect"]}]
},
"detect": {"height": 1080, "width": 1920, "fps": 5},
},
},
}
ADMIN_PASSWORD = "admin-real-password"
NEW_PASSWORD = "AttackerChosenPassword123!"
class TestUpdatePasswordAccess(BaseTestHttp):
def setUp(self):
super().setUp([Event, ReviewSegment, Recordings, User])
self.minimal_config = _CUSTOM_ROLE_CONFIG
self.app = super().create_app()
User.insert(
username="admin",
password_hash=hash_password(ADMIN_PASSWORD, iterations=10),
role="admin",
notification_tokens=[],
).execute()
async def mock_get_current_user(request: Request):
return {
"username": request.headers.get("remote-user"),
"role": request.headers.get("remote-role"),
}
self.app.dependency_overrides[get_current_user] = mock_get_current_user
def tearDown(self):
self.app.dependency_overrides.clear()
super().tearDown()
def _change_password(self, actor: str, role: str, target: str, old_password: str):
with AuthTestClient(self.app) as client:
return client.put(
f"/users/{target}/password",
json={"password": NEW_PASSWORD, "old_password": old_password},
headers={"remote-user": actor, "remote-role": role},
)
def _admin_password_unchanged(self) -> bool:
return verify_password(ADMIN_PASSWORD, User.get_by_id("admin").password_hash)
def test_custom_role_cannot_target_another_account(self):
resp = self._change_password("neighbor", "neighbor", "admin", "wrong-guess")
assert resp.status_code == 403
assert self._admin_password_unchanged()
def test_custom_role_cannot_target_another_account_with_correct_password(self):
# The 403 must land before old_password is checked, so knowing the
# target's password is not a way through
resp = self._change_password("neighbor", "neighbor", "admin", ADMIN_PASSWORD)
assert resp.status_code == 403
assert self._admin_password_unchanged()
def test_viewer_cannot_target_another_account(self):
resp = self._change_password("viewer_user", "viewer", "admin", ADMIN_PASSWORD)
assert resp.status_code == 403
assert self._admin_password_unchanged()
def test_admin_can_target_another_account(self):
User.insert(
username="neighbor",
password_hash=hash_password("neighbor-password", iterations=10),
role="neighbor",
notification_tokens=[],
).execute()
resp = self._change_password("admin", "admin", "neighbor", "")
assert resp.status_code == 200
def test_non_admin_can_change_own_password(self):
User.insert(
username="neighbor",
password_hash=hash_password("neighbor-password", iterations=10),
role="neighbor",
notification_tokens=[],
).execute()
resp = self._change_password(
"neighbor", "neighbor", "neighbor", "neighbor-password"
)
assert resp.status_code == 200
def test_non_admin_own_password_still_requires_old_password(self):
User.insert(
username="neighbor",
password_hash=hash_password("neighbor-password", iterations=10),
role="neighbor",
notification_tokens=[],
).execute()
resp = self._change_password("neighbor", "neighbor", "neighbor", "wrong-guess")
assert resp.status_code == 401
+75
View File
@@ -0,0 +1,75 @@
"""Tests for audio label mapping."""
import threading
import unittest
from unittest.mock import Mock
import numpy as np
from frigate.events.audio import AudioTfl
class TestAudioTfl(unittest.TestCase):
def setUp(self):
self.detector = AudioTfl.__new__(AudioTfl)
self.detector.stop_event = threading.Event()
self.detector._default_labels = {
69: "dog",
70: "bark",
75: "whimper_dog",
117: "dogs",
}
def test_update_labelmap_replaces_and_resets_overrides(self):
self.detector.update_labelmap({69: "dogs", 70: "dogs"})
assert self.detector.labels == {
69: "dogs",
70: "dogs",
75: "whimper_dog",
117: "dogs",
}
self.detector.update_labelmap({75: "whimper"})
assert self.detector.labels == {
69: "dog",
70: "bark",
75: "whimper",
117: "dogs",
}
def test_detect_returns_highest_scoring_detection_for_grouped_label(self):
self.detector.update_labelmap({69: "dogs", 70: "dogs", 75: "dogs"})
self.detector._detect_raw = Mock(
return_value=np.array(
[
[117, 0.95, -1, -1, -1, -1],
[70, 0.9, -1, -1, -1, -1],
[69, 0.8, -1, -1, -1, -1],
[75, 0.7, -1, -1, -1, -1],
],
dtype=np.float32,
)
)
detections = self.detector.detect(np.array([], dtype=np.float32))
assert len(detections) == 1
assert detections[0][0] == "dogs"
self.assertAlmostEqual(detections[0][1], 0.95)
def test_each_dog_audio_label_maps_to_grouped_label(self):
self.detector.update_labelmap({69: "dogs", 70: "dogs", 75: "dogs"})
for class_id in (69, 70, 75):
with self.subTest(class_id=class_id):
self.detector._detect_raw = Mock(
return_value=np.array(
[[class_id, 0.9, -1, -1, -1, -1]], dtype=np.float32
)
)
detections = self.detector.detect(np.array([], dtype=np.float32))
assert len(detections) == 1
assert detections[0][0] == "dogs"
self.assertAlmostEqual(detections[0][1], 0.9)
+471 -4
View File
@@ -1,13 +1,75 @@
"""Test camera user and password cleanup."""
"""Tests for Birdseye canvas sizing and layout behavior."""
import multiprocessing as mp
import unittest
from unittest.mock import Mock
from frigate.config import FrigateConfig
from frigate.output.birdseye import BirdsEyeFrameManager, get_canvas_shape
from frigate.config import (
BirdseyeModeEnum,
FrigateConfig,
birdseye_modes_from_mqtt_payload,
birdseye_modes_to_mqtt_payload,
)
from frigate.output.birdseye import (
Birdseye,
BirdseyeActivity,
BirdsEyeFrameManager,
get_canvas_shape,
)
class TestBirdseye(unittest.TestCase):
def _build_manager(
self, camera_dimensions: dict[str, tuple[int, int]]
) -> BirdsEyeFrameManager:
config = {
"mqtt": {"host": "mqtt"},
"birdseye": {"width": 1280, "height": 720},
"cameras": {},
}
for order, (camera, dimensions) in enumerate(
camera_dimensions.items(), start=1
):
config["cameras"][camera] = {
"ffmpeg": {
"inputs": [
{
"path": f"rtsp://10.0.0.1:554/{camera}",
"roles": ["detect"],
}
]
},
"detect": {
"width": dimensions[0],
"height": dimensions[1],
"fps": 5,
},
"birdseye": {"order": order},
}
return BirdsEyeFrameManager(FrigateConfig(**config), mp.Event())
def _assert_no_overlaps(
self, layout: list[list[tuple[str, tuple[int, int, int, int]]]]
):
rectangles = [position for row in layout for _, position in row]
for index, rect in enumerate(rectangles):
x1, y1, width1, height1 = rect
for other in rectangles[index + 1 :]:
x2, y2, width2, height2 = other
overlap = (
x1 < x2 + width2
and x2 < x1 + width1
and y1 < y2 + height2
and y2 < y1 + height1
)
self.assertFalse(
overlap,
msg=f"Overlapping rectangles found: {rect} and {other}",
)
def test_16x9(self):
"""Test 16x9 aspect ratio works as expected for birdseye."""
width = 1280
@@ -48,6 +110,258 @@ class TestBirdseye(unittest.TestCase):
assert canvas_width == width # width will be the same
assert canvas_height != height
def test_portrait_camera_does_not_overlap_next_row(self):
"""Portrait cameras should reserve their real horizontal position on the next row."""
manager = self._build_manager(
{
"cam_a": (1280, 720),
"cam_p": (360, 640),
"cam_b": (1280, 720),
"cam_c": (640, 480),
}
)
layout = manager.calculate_layout(["cam_a", "cam_p", "cam_b", "cam_c"], 3)
self.assertIsNotNone(layout)
assert layout is not None
self._assert_no_overlaps(layout)
cam_c = [
position for row in layout for camera, position in row if camera == "cam_c"
][0]
self.assertEqual(cam_c[0], 0)
def test_portrait_reservation_only_applies_to_next_row(self):
"""Portrait reservations should not push later rows after the span ends."""
manager = self._build_manager(
{
"cam_a": (1280, 720),
"cam_p": (360, 640),
"cam_b": (1280, 720),
"cam_c": (1280, 720),
"cam_d": (1280, 720),
"cam_e": (1280, 720),
}
)
layout = manager.calculate_layout(
["cam_a", "cam_p", "cam_b", "cam_c", "cam_d", "cam_e"],
3,
)
self.assertIsNotNone(layout)
assert layout is not None
self._assert_no_overlaps(layout)
cam_e = [
position for row in layout for camera, position in row if camera == "cam_e"
][0]
self.assertEqual(cam_e[0], 0)
def test_multiple_portraits_reserve_distinct_ranges(self):
"""Multiple portrait cameras in one row should reserve separate spans below them."""
manager = self._build_manager(
{
"cam_a": (640, 480),
"cam_p1": (360, 640),
"cam_p2": (360, 640),
"cam_b": (640, 480),
"cam_c": (1280, 720),
"cam_d": (640, 480),
}
)
layout = manager.calculate_layout(
["cam_a", "cam_p1", "cam_p2", "cam_b", "cam_c", "cam_d"],
4,
)
self.assertIsNotNone(layout)
assert layout is not None
self._assert_no_overlaps(layout)
def test_two_landscapes_then_portrait_then_two_landscapes(self):
"""A portrait after two landscapes should reserve only its own tail span."""
manager = self._build_manager(
{
"cam_a": (1280, 720),
"cam_b": (1280, 720),
"cam_p": (360, 640),
"cam_c": (1280, 720),
"cam_d": (1280, 720),
}
)
layout = manager.calculate_layout(
["cam_a", "cam_b", "cam_p", "cam_c", "cam_d"],
3,
)
self.assertIsNotNone(layout)
assert layout is not None
self._assert_no_overlaps(layout)
cam_c = [
position for row in layout for camera, position in row if camera == "cam_c"
][0]
cam_d = [
position for row in layout for camera, position in row if camera == "cam_d"
][0]
self.assertEqual(cam_c[0], 0)
self.assertEqual(cam_d[0], cam_c[0] + cam_c[2])
class TestBirdseyeActivity(unittest.TestCase):
"""Test which camera activity is included in each Birdseye mode."""
def setUp(self):
config = {
"mqtt": {"enabled": False},
"birdseye": {
"enabled": True,
"modes": ["motion", "all_objects"],
},
"cameras": {
"front": {
"ffmpeg": {
"inputs": [
{"path": "rtsp://10.0.0.1:554/video", "roles": ["detect"]}
]
},
"detect": {"height": 1080, "width": 1920, "fps": 5},
}
},
}
self.manager = BirdsEyeFrameManager(FrigateConfig(**config), mp.Event())
def test_each_mode_matches_only_its_own_activity(self):
motion_activity = BirdseyeActivity(
has_object=False, has_motion=True, severity=None
)
object_activity = BirdseyeActivity(
has_object=True, has_motion=False, severity=None
)
no_activity = BirdseyeActivity(
has_object=False, has_motion=False, severity=None
)
assert self.manager.camera_threshold_active(
[BirdseyeModeEnum.motion], motion_activity
)
assert not self.manager.camera_threshold_active(
[BirdseyeModeEnum.motion], object_activity
)
assert self.manager.camera_threshold_active(
[BirdseyeModeEnum.all_objects], object_activity
)
assert not self.manager.camera_threshold_active(
[BirdseyeModeEnum.all_objects], motion_activity
)
assert self.manager.camera_live_active(
[BirdseyeModeEnum.continuous], no_activity
)
def test_continuous_is_not_threshold_activity(self):
no_activity = BirdseyeActivity(
has_object=False, has_motion=False, severity=None
)
assert not self.manager.camera_threshold_active(
[BirdseyeModeEnum.continuous], no_activity
)
def test_modes_can_be_combined(self):
modes = [BirdseyeModeEnum.motion, BirdseyeModeEnum.all_objects]
assert self.manager.camera_threshold_active(
modes, BirdseyeActivity(has_object=False, has_motion=True, severity=None)
)
assert self.manager.camera_threshold_active(
modes, BirdseyeActivity(has_object=True, has_motion=False, severity=None)
)
assert not self.manager.camera_threshold_active(
modes, BirdseyeActivity(has_object=False, has_motion=False, severity=None)
)
def test_empty_modes_never_activate(self):
activity = BirdseyeActivity(has_object=True, has_motion=True, severity=None)
assert not self.manager.camera_threshold_active([], activity)
assert not self.manager.camera_live_active([], activity)
def test_alerts_and_detections_match_review_severity(self):
alert = BirdseyeActivity(has_object=False, has_motion=False, severity="alert")
detection = BirdseyeActivity(
has_object=False, has_motion=False, severity="detection"
)
idle = BirdseyeActivity(has_object=False, has_motion=False, severity=None)
assert self.manager.camera_live_active([BirdseyeModeEnum.alerts], alert)
assert not self.manager.camera_live_active([BirdseyeModeEnum.alerts], detection)
assert not self.manager.camera_live_active([BirdseyeModeEnum.alerts], idle)
assert self.manager.camera_live_active([BirdseyeModeEnum.detections], detection)
assert not self.manager.camera_live_active([BirdseyeModeEnum.detections], alert)
def test_review_severity_is_not_threshold_activity(self):
alert = BirdseyeActivity(has_object=False, has_motion=False, severity="alert")
assert not self.manager.camera_threshold_active(
[BirdseyeModeEnum.alerts, BirdseyeModeEnum.motion], alert
)
def test_all_objects_covers_active_and_stationary_objects(self):
birdseye = Birdseye.__new__(Birdseye)
birdseye.birdseye_manager = Mock()
birdseye.birdseye_manager.update.return_value = (False, False)
birdseye._idle_interval = None
birdseye.review_severity = {}
frame = Mock()
birdseye.write_data(
"front",
[
{"stationary": True, "false_positive": True},
{"stationary": True, "false_positive": False},
],
[[0, 0, 10, 10]],
1.0,
frame,
)
birdseye.birdseye_manager.update.assert_called_once_with(
"front",
BirdseyeActivity(has_object=True, has_motion=True, severity=None),
1.0,
frame,
)
def test_false_positives_do_not_count_as_objects(self):
birdseye = Birdseye.__new__(Birdseye)
birdseye.birdseye_manager = Mock()
birdseye.birdseye_manager.update.return_value = (False, False)
birdseye._idle_interval = None
birdseye.review_severity = {}
frame = Mock()
birdseye.write_data(
"front",
[
{"stationary": True, "false_positive": True},
{"stationary": False, "false_positive": True},
],
[],
1.0,
frame,
)
birdseye.birdseye_manager.update.assert_called_once_with(
"front",
BirdseyeActivity(has_object=False, has_motion=False, severity=None),
1.0,
frame,
)
class TestBirdseyeCameraOrder(unittest.TestCase):
"""Test that birdseye reacts to camera order changes without a restart."""
@@ -55,7 +369,7 @@ class TestBirdseyeCameraOrder(unittest.TestCase):
def setUp(self):
config = {
"mqtt": {"enabled": False},
"birdseye": {"enabled": True, "mode": "continuous"},
"birdseye": {"enabled": True, "modes": ["continuous"]},
"cameras": {
camera: {
"ffmpeg": {
@@ -77,6 +391,7 @@ class TestBirdseyeCameraOrder(unittest.TestCase):
camera_data["current_frame"] = None
camera_data["current_frame_time"] = 1.0
camera_data["last_active_frame"] = 1.0
camera_data["live_active"] = True
def layout_order(self) -> list[str]:
"""Return the cameras in the order the current layout renders them."""
@@ -114,3 +429,155 @@ class TestBirdseyeCameraOrder(unittest.TestCase):
assert not layout_changed
assert self.layout_order() == ["back", "front", "side"]
class TestBirdseyeLiveActivity(unittest.TestCase):
"""Test that live activity bypasses the inactivity threshold."""
def setUp(self):
config = {
"mqtt": {"enabled": False},
"birdseye": {
"enabled": True,
"modes": ["continuous"],
"inactivity_threshold": 30,
},
"cameras": {
camera: {
"ffmpeg": {
"inputs": [
{"path": "rtsp://10.0.0.1:554/video", "roles": ["detect"]}
]
},
"detect": {"height": 1080, "width": 1920, "fps": 5},
}
for camera in ("back", "front")
},
}
self.config = FrigateConfig(**config)
self.manager = BirdsEyeFrameManager(self.config, mp.Event())
for camera_data in self.manager.cameras.values():
camera_data["current_frame"] = None
camera_data["current_frame_time"] = 1000.0
camera_data["last_active_frame"] = 0.0
camera_data["live_active"] = False
def test_live_active_camera_is_shown_without_a_recent_active_frame(self):
self.manager.cameras["front"]["live_active"] = True
self.manager.update_frame()
assert self.manager.active_cameras == {"front"}
def test_live_active_camera_drops_out_immediately(self):
self.manager.cameras["front"]["live_active"] = True
self.manager.update_frame()
assert self.manager.active_cameras == {"front"}
self.manager.cameras["front"]["live_active"] = False
self.manager.update_frame()
assert self.manager.active_cameras == set()
def test_threshold_activity_lingers_then_expires(self):
self.manager.cameras["front"]["last_active_frame"] = 980.0
self.manager.update_frame()
assert self.manager.active_cameras == {"front"}
self.manager.cameras["front"]["last_active_frame"] = 960.0
self.manager.update_frame()
assert self.manager.active_cameras == set()
def test_max_cameras_ranks_live_active_cameras_first(self):
self.config.birdseye.layout.max_cameras = 1
self.manager.cameras["front"]["live_active"] = True
self.manager.cameras["back"]["last_active_frame"] = 995.0
self.manager.update_frame()
assert self.manager.active_cameras == {"front"}
class TestBirdseyeModePayload(unittest.TestCase):
"""Test the MQTT payload contract for Birdseye activity modes."""
def test_single_mode_round_trips(self):
modes = birdseye_modes_from_mqtt_payload("ALERTS")
assert modes == [BirdseyeModeEnum.alerts]
assert birdseye_modes_to_mqtt_payload(modes) == "ALERTS"
def test_combined_modes_are_published_in_enum_order(self):
modes = birdseye_modes_from_mqtt_payload("ALERTS,MOTION")
assert modes == [BirdseyeModeEnum.alerts, BirdseyeModeEnum.motion]
assert birdseye_modes_to_mqtt_payload(modes) == "MOTION,ALERTS"
def test_none_round_trips_to_an_empty_list(self):
assert birdseye_modes_from_mqtt_payload("NONE") == []
assert birdseye_modes_to_mqtt_payload([]) == "NONE"
def test_invalid_payloads_are_rejected(self):
for payload in (
"UNKNOWN",
"motion",
"MOTION_OBJECTS",
"NONE,MOTION",
"MOTION,MOTION",
"MOTION,",
"",
):
with self.subTest(payload=payload):
assert birdseye_modes_from_mqtt_payload(payload) is None
class TestBirdseyeReviewSeverity(unittest.TestCase):
"""Test that review updates drive the per-camera severity map."""
def setUp(self):
self.birdseye = Birdseye.__new__(Birdseye)
self.birdseye.review_subscriber = Mock()
self.birdseye.review_severity = {}
self.birdseye.birdseye_manager = Mock()
self.birdseye.birdseye_manager.update.return_value = (False, False)
self.birdseye._idle_interval = None
def _drain(self, *updates):
self.birdseye.review_subscriber.check_for_update.side_effect = [*updates, None]
self.birdseye.check_review_updates()
def test_new_segment_sets_severity(self):
self._drain({"type": "new", "after": {"camera": "front", "severity": "alert"}})
assert self.birdseye.review_severity == {"front": "alert"}
def test_update_upgrades_severity(self):
self._drain(
{"type": "new", "after": {"camera": "front", "severity": "detection"}},
{"type": "update", "after": {"camera": "front", "severity": "alert"}},
)
assert self.birdseye.review_severity == {"front": "alert"}
def test_end_clears_severity(self):
self._drain(
{"type": "new", "after": {"camera": "front", "severity": "alert"}},
{"type": "end", "after": {"camera": "front", "severity": "alert"}},
)
assert self.birdseye.review_severity == {}
def test_write_data_passes_the_tracked_severity(self):
self.birdseye.review_severity = {"front": "alert"}
frame = Mock()
self.birdseye.write_data("front", [], [], 1.0, frame)
self.birdseye.birdseye_manager.update.assert_called_once_with(
"front",
BirdseyeActivity(has_object=False, has_motion=False, severity="alert"),
1.0,
frame,
)
+154
View File
@@ -0,0 +1,154 @@
"""Tests for dynamic camera config updates recreating ffmpeg commands."""
import unittest
from unittest.mock import patch
from frigate.config import CameraConfig, FrigateConfig
from frigate.config.camera.updater import (
CameraConfigUpdateEnum,
CameraConfigUpdateSubscriber,
)
from frigate.const import SUB_CACHE_TAG
from frigate.detectors.detector_config import SceneEnum
def _build_scene_frigate_config(scene: str | None) -> FrigateConfig:
detect = {"height": 1080, "width": 1920, "fps": 5}
if scene is not None:
detect["scene"] = scene
return FrigateConfig(
**{
"mqtt": {"host": "mqtt"},
"models": [
{"devices": ["cpu"]},
{"scene": "outdoor", "devices": ["openvino:CPU"]},
],
"cameras": {
"front_door": {
"ffmpeg": {
"inputs": [
{"path": "rtsp://10.0.0.1:554/video", "roles": ["detect"]}
]
},
"detect": detect,
}
},
}
)
def _build_camera_config(sub_enabled: bool) -> CameraConfig:
config = FrigateConfig(
**{
"mqtt": {"host": "mqtt"},
"cameras": {
"front_door": {
"ffmpeg": {
"inputs": [
{
"path": "rtsp://10.0.0.1:554/video",
"roles": ["detect", "record"],
},
{
"path": "rtsp://10.0.0.1:554/video2",
"roles": ["record_sub"],
},
]
},
"record": {"enabled": True, "sub": {"enabled": sub_enabled}},
}
},
}
)
return config.cameras["front_door"]
def _has_sub_output(camera_config: CameraConfig) -> bool:
return any(
SUB_CACHE_TAG in part for c in camera_config.ffmpeg_cmds for part in c["cmd"]
)
class TestRecordUpdateRecreatesFfmpegCmds(unittest.TestCase):
def setUp(self):
# avoid binding a real ZMQ socket; updates are fed directly through
# the mocked subscriber below
patcher = patch("frigate.config.camera.updater.ConfigSubscriber")
patcher.start()
self.addCleanup(patcher.stop)
def _push_record_update(
self, subscriber: CameraConfigUpdateSubscriber, record_config
) -> None:
subscriber.subscriber.check_for_update.side_effect = [
("config/cameras/front_door/record", record_config),
(None, None),
]
subscriber.check_for_updates()
def test_enabling_sub_recreates_ffmpeg_cmds(self):
camera_config = _build_camera_config(sub_enabled=False)
subscriber = CameraConfigUpdateSubscriber(
None, {"front_door": camera_config}, [CameraConfigUpdateEnum.record]
)
assert not _has_sub_output(camera_config)
self._push_record_update(
subscriber, _build_camera_config(sub_enabled=True).record
)
assert _has_sub_output(camera_config)
def test_disabling_sub_recreates_ffmpeg_cmds(self):
camera_config = _build_camera_config(sub_enabled=True)
subscriber = CameraConfigUpdateSubscriber(
None, {"front_door": camera_config}, [CameraConfigUpdateEnum.record]
)
assert _has_sub_output(camera_config)
self._push_record_update(
subscriber, _build_camera_config(sub_enabled=False).record
)
assert not _has_sub_output(camera_config)
@patch("frigate.detectors.detector_config.load_labels")
def test_removed_camera_readded_without_scene_gets_fresh_model(self, mock_labels):
mock_labels.return_value = {}
config = _build_scene_frigate_config("outdoor")
subscriber = CameraConfigUpdateSubscriber(
config, {}, [CameraConfigUpdateEnum.add, CameraConfigUpdateEnum.remove]
)
assert config.model_for_camera("front_door").scene == SceneEnum.outdoor
subscriber.subscriber.check_for_update.side_effect = [
("config/cameras/front_door/remove", config.cameras["front_door"]),
(None, None),
]
subscriber.check_for_updates()
# recreating the camera through the wizard leaves the scene unset,
# so the removed camera's cached model must not carry over
readded = _build_scene_frigate_config(None).cameras["front_door"]
subscriber.subscriber.check_for_update.side_effect = [
("config/cameras/front_door/add", readded),
(None, None),
]
subscriber.check_for_updates()
assert config.model_for_camera("front_door").scene == SceneEnum.all
def test_unchanged_record_update_keeps_existing_cmds(self):
camera_config = _build_camera_config(sub_enabled=False)
subscriber = CameraConfigUpdateSubscriber(
None, {"front_door": camera_config}, [CameraConfigUpdateEnum.record]
)
cmds_before = camera_config.ffmpeg_cmds
# neither enabled_in_config nor sub.enabled changed, so the
# commands should not be rebuilt
self._push_record_update(
subscriber, _build_camera_config(sub_enabled=False).record
)
assert camera_config.ffmpeg_cmds is cmds_before
+227
View File
@@ -0,0 +1,227 @@
"""Regression tests for runtime camera add and delete handling."""
import asyncio
import threading
import unittest
from types import SimpleNamespace
from unittest.mock import MagicMock
# LicensePlatePostProcessor is imported via the maintainer rather than from
# data_processing.post.license_plate, which circularly imports back through
# frigate.embeddings before that package finishes initializing
from frigate.embeddings.maintainer import (
EmbeddingMaintainer,
LicensePlatePostProcessor,
)
from frigate.ptz.autotrack import PtzAutoTracker
from frigate.review.maintainer import ReviewSegmentMaintainer
from frigate.track.object_processing import TrackedObjectProcessor
def _make_processor() -> TrackedObjectProcessor:
"""Build a processor with no cameras, bypassing __init__."""
processor = TrackedObjectProcessor.__new__(TrackedObjectProcessor)
processor.camera_states = {}
processor.camera_states_lock = threading.Lock()
processor.config = SimpleNamespace(cameras={})
processor.event_sender = MagicMock()
processor.detection_publisher = MagicMock()
processor.ongoing_manual_events = {}
return processor
class TestObjectProcessorUnknownCamera(unittest.TestCase):
def test_save_lpr_snapshot_ignores_unknown_camera(self):
processor = _make_processor()
# 1x1 png, base64; decoding must not be what fails
payload = (
"iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mP8z8BQDwAEhQGAhKmMIQAAAABJRU5ErkJggg==",
"1234.5-abcdef",
"deleted_cam",
)
processor.save_lpr_snapshot(payload)
processor.event_sender.publish.assert_not_called()
def test_create_manual_event_ignores_unknown_camera(self):
processor = _make_processor()
payload = (
1234.5,
"deleted_cam",
"person",
"1234.5-abcdef",
True,
0.9,
None,
None,
"api",
False,
None,
)
processor.create_manual_event(payload)
processor.event_sender.publish.assert_not_called()
self.assertEqual(processor.ongoing_manual_events, {})
def test_create_lpr_event_ignores_unknown_camera(self):
processor = _make_processor()
payload = (
1234.5,
"deleted_cam",
"license_plate",
"1234.5-abcdef",
True,
0.9,
None,
"ABC123",
)
processor.create_lpr_event(payload)
processor.event_sender.publish.assert_not_called()
self.assertEqual(processor.ongoing_manual_events, {})
def test_create_manual_event_ignores_camera_added_but_not_yet_drained(self):
"""The add window: present in config.cameras, absent from camera_states.
debug_replay writes the camera into the shared config before publishing
add, so a guard on config.cameras passes here and falls through to
camera_states. This test fails against such a guard.
"""
processor = _make_processor()
processor.config = SimpleNamespace(
cameras={
"new_cam": SimpleNamespace(
record=SimpleNamespace(event_pre_capture=5, enabled=True)
)
}
)
payload = (
1234.5,
"new_cam",
"person",
"1234.5-abcdef",
True,
0.9,
None,
None,
"api",
False,
None,
)
processor.create_manual_event(payload)
processor.event_sender.publish.assert_not_called()
class TestEmbeddingsUnknownCamera(unittest.TestCase):
def _make_maintainer(self) -> EmbeddingMaintainer:
maintainer = EmbeddingMaintainer.__new__(EmbeddingMaintainer)
maintainer.config = SimpleNamespace(cameras={})
maintainer.event_end_subscriber = MagicMock()
maintainer.realtime_processors = [MagicMock()]
# spec is required: the dispatch loop is a chain of isinstance checks,
# and a bare MagicMock matches none of them, so the crashing branch
# would never run and the test would pass against unfixed code
maintainer.post_processors = [MagicMock(spec=LicensePlatePostProcessor)]
maintainer.detected_license_plates = {"1234.5-abcdef": {"obj_data": {}}}
maintainer.recordings_available_through = {"deleted_cam": 1234.5}
maintainer.event_metadata_publisher = MagicMock()
return maintainer
def test_process_finalized_skips_unknown_camera(self):
maintainer = self._make_maintainer()
# updated_db=False bypasses the Event.get branch, which would hit the
# database and mask the KeyError this test is about
maintainer.event_end_subscriber.check_for_update.side_effect = [
("1234.5-abcdef", "deleted_cam", False),
None,
]
maintainer._process_finalized()
maintainer.post_processors[0].process_data.assert_not_called()
def test_process_finalized_still_expires_realtime_state(self):
"""The guard must not skip per-event cleanup, only post processing."""
maintainer = self._make_maintainer()
maintainer.event_end_subscriber.check_for_update.side_effect = [
("1234.5-abcdef", "deleted_cam", False),
None,
]
maintainer._process_finalized()
maintainer.realtime_processors[0].expire_object.assert_called_once_with(
"1234.5-abcdef", "deleted_cam"
)
def test_expire_dedicated_lpr_drops_entry_for_unknown_camera(self):
maintainer = self._make_maintainer()
maintainer.detected_license_plates = {
"1234.5-abcdef": {"camera": "deleted_cam", "last_seen": 1.0}
}
maintainer._expire_dedicated_lpr()
self.assertEqual(maintainer.detected_license_plates, {})
class TestReviewMaintainerRemoval(unittest.TestCase):
def test_camera_removal_ends_segment_and_clears_state(self):
maintainer = ReviewSegmentMaintainer.__new__(ReviewSegmentMaintainer)
maintainer.active_review_segments = {"deleted_cam": MagicMock()}
maintainer.indefinite_events = {"deleted_cam": {"1234.5-abcdef": 1.0}}
maintainer.forcibly_end_segment = MagicMock()
maintainer._handle_camera_removed("deleted_cam")
maintainer.forcibly_end_segment.assert_called_once_with("deleted_cam")
self.assertNotIn("deleted_cam", maintainer.indefinite_events)
class TestAutotrackerMoveQueue(unittest.TestCase):
def test_move_queue_drops_move_for_removed_camera(self):
tracker = PtzAutoTracker.__new__(PtzAutoTracker)
tracker.stop_event = MagicMock()
# one pass through the loop, then stop
tracker.stop_event.is_set.side_effect = [False, True]
tracker.ptz_metrics = {}
tracker.move_queues = {"deleted_cam": asyncio.Queue()}
tracker.move_queue_locks = {"deleted_cam": asyncio.Lock()}
tracker.onvif = MagicMock()
tracker.config = SimpleNamespace(cameras={})
tracker.move_queues["deleted_cam"].put_nowait((1234.5, 0.1, 0.1, 0.0))
asyncio.run(tracker._process_move_queue("deleted_cam"))
tracker.onvif._move_relative.assert_not_called()
class TestCameraStateAccessors(unittest.TestCase):
def test_get_camera_state_returns_none_for_unknown_camera(self):
processor = _make_processor()
self.assertIsNone(processor.get_camera_state("deleted_cam"))
def test_get_camera_states_returns_a_snapshot_not_a_view(self):
"""A live values() view raises RuntimeError if the writer pops mid-iteration."""
processor = _make_processor()
processor.camera_states = {"one": MagicMock(), "two": MagicMock()}
states = processor.get_camera_states()
processor.camera_states.pop("one")
self.assertEqual(len(states), 2)
def test_get_current_frame_time_is_zero_for_unknown_camera(self):
processor = _make_processor()
self.assertEqual(processor.get_current_frame_time("deleted_cam"), 0.0)
+171
View File
@@ -0,0 +1,171 @@
"""Tests for the recording clip download stream."""
import os
import subprocess as sp
import sys
import tempfile
import threading
import unittest
from unittest.mock import patch
from frigate.api.media import _run_clip_download
# more than the 64 KB a pipe holds, so an undrained stderr blocks ffmpeg
STDERR_FLOOD_BYTES = 256 * 1024
PAYLOAD = b"0123456789" * 512
def fake_ffmpeg(*statements: str) -> list[str]:
"""Build an argv that stands in for ffmpeg, running the given statements."""
return [sys.executable, "-c", "\n".join(("import sys, time", *statements))]
class TestRunClipDownload(unittest.TestCase):
def setUp(self):
handle, self.playlist_path = tempfile.mkstemp(suffix=".txt")
os.close(handle)
def tearDown(self):
if os.path.exists(self.playlist_path):
os.unlink(self.playlist_path)
def collect(self, ffmpeg_cmd: list[str], timeout: float = 30.0) -> bytes:
"""Drain the generator on a worker thread so a deadlock fails the test."""
chunks: list[bytes] = []
errors: list[BaseException] = []
def drain() -> None:
try:
chunks.extend(_run_clip_download(ffmpeg_cmd, self.playlist_path))
except BaseException as err:
errors.append(err)
thread = threading.Thread(target=drain, daemon=True)
thread.start()
thread.join(timeout)
self.assertFalse(
thread.is_alive(), "clip download did not finish, ffmpeg is deadlocked"
)
if errors:
raise errors[0]
return b"".join(chunks)
def test_streams_full_clip_when_ffmpeg_floods_stderr(self):
"""A warning flood past the pipe buffer must not stall the download."""
data = self.collect(
fake_ffmpeg(
f"sys.stderr.write('w' * {STDERR_FLOOD_BYTES})",
"sys.stderr.flush()",
f"sys.stdout.buffer.write({PAYLOAD!r})",
)
)
self.assertEqual(data, PAYLOAD)
self.assertFalse(os.path.exists(self.playlist_path))
def test_streams_clip_written_before_stderr_flood(self):
data = self.collect(
fake_ffmpeg(
f"sys.stdout.buffer.write({PAYLOAD!r})",
"sys.stdout.flush()",
f"sys.stderr.write('w' * {STDERR_FLOOD_BYTES})",
)
)
self.assertEqual(data, PAYLOAD)
def test_logs_ffmpeg_output_and_removes_playlist_on_failure(self):
with patch("frigate.api.media.logger") as logger:
data = self.collect(
fake_ffmpeg(
"sys.stderr.write('something went wrong')",
"sys.exit(1)",
)
)
self.assertEqual(data, b"")
logger.error.assert_called_once()
self.assertIn("something went wrong", logger.error.call_args.args[1])
self.assertFalse(os.path.exists(self.playlist_path))
def test_logs_only_the_tail_of_a_flooded_stderr(self):
with patch("frigate.api.media.logger") as logger:
self.collect(
fake_ffmpeg(
f"sys.stderr.write('w' * {STDERR_FLOOD_BYTES})",
"sys.exit(1)",
)
)
logged = logger.error.call_args.args[1]
self.assertLess(len(logged), STDERR_FLOOD_BYTES)
def test_does_not_log_a_successful_download(self):
with patch("frigate.api.media.logger") as logger:
self.collect(fake_ffmpeg(f"sys.stdout.buffer.write({PAYLOAD!r})"))
logger.error.assert_not_called()
def test_removes_playlist_when_ffmpeg_cannot_start(self):
with self.assertRaises(OSError):
self.collect(["/nonexistent-ffmpeg-binary"])
self.assertFalse(os.path.exists(self.playlist_path))
def test_closes_the_stdout_pipe_after_a_successful_download(self):
processes: list[sp.Popen] = []
real_popen = sp.Popen
def spy(*args, **kwargs):
process = real_popen(*args, **kwargs)
processes.append(process)
return process
with patch("subprocess.Popen", spy):
self.collect(fake_ffmpeg(f"sys.stdout.buffer.write({PAYLOAD!r})"))
self.assertTrue(processes[0].stdout.closed)
def test_terminating_a_lingering_ffmpeg_is_not_logged_as_a_failure(self):
"""A complete download whose ffmpeg overstays is a success, not an error."""
lingering = fake_ffmpeg(
"import os",
f"os.write(1, {PAYLOAD!r})",
"os.close(1)",
"time.sleep(30)",
)
with patch("frigate.api.media.CLIP_FFMPEG_EXIT_TIMEOUT", 0.5):
with patch("frigate.api.media.logger") as logger:
data = self.collect(lingering)
self.assertEqual(data, PAYLOAD)
logger.error.assert_not_called()
def test_client_disconnect_kills_ffmpeg_and_removes_playlist(self):
processes: list[sp.Popen] = []
real_popen = sp.Popen
def spy(*args, **kwargs):
process = real_popen(*args, **kwargs)
processes.append(process)
return process
forever = fake_ffmpeg(
"while True:",
" sys.stdout.buffer.write(b'x' * 4096)",
" sys.stdout.flush()",
)
with patch("subprocess.Popen", spy):
stream = _run_clip_download(forever, self.playlist_path)
self.assertTrue(next(stream))
# Starlette never closes the generator itself, so a real disconnect
# reaches this path only once the frame is finalized
stream.close()
self.assertIsNotNone(processes[0].poll(), "ffmpeg outlived the request")
self.assertFalse(os.path.exists(self.playlist_path))
+484 -61
View File
@@ -1,15 +1,18 @@
import json
import os
import unittest
from copy import deepcopy
from unittest.mock import patch
import numpy as np
from pydantic import ValidationError
from ruamel.yaml.constructor import DuplicateKeyError
from frigate.config import BirdseyeModeEnum, FrigateConfig
from frigate.config import BirdseyeModeEnum, FrigateConfig, RetainModeEnum
from frigate.const import MODEL_CACHE_DIR
from frigate.detectors import DetectorTypeEnum
from frigate.detectors.detector_config import SceneEnum
from frigate.detectors.device import build_detector_config, runner_names
from frigate.util.builtin import deep_merge
@@ -64,49 +67,236 @@ class TestConfig(unittest.TestCase):
def test_config_class(self):
frigate_config = FrigateConfig(**self.minimal)
assert "cpu" in frigate_config.detectors.keys()
assert frigate_config.detectors["cpu"].type == DetectorTypeEnum.cpu
assert frigate_config.detectors["cpu"].model.width == 320
model = frigate_config.primary_model
assert model.scene == SceneEnum.all
assert model.width == 320
assert frigate_config.devices_for_model(model)[0].detector == (
DetectorTypeEnum.cpu
)
@patch("frigate.detectors.detector_config.load_labels")
def test_detector_custom_model_path(self, mock_labels):
def test_model_custom_path(self, mock_labels):
mock_labels.return_value = {}
config = {
"detectors": {
"cpu": {
"type": "cpu",
"model_path": "/cpu_model.tflite",
"models": [
# needs to be a file that will exist, doesn't matter what
{"path": "/etc/hosts", "width": 512, "devices": ["openvino:GPU"]},
],
}
frigate_config = FrigateConfig(**(deep_merge(config, self.minimal)))
model = frigate_config.primary_model
assert model.path == "/etc/hosts"
assert model.width == 512
detector_config = build_detector_config(
frigate_config.devices_for_model(model)[0], model
)
assert detector_config.type == DetectorTypeEnum.openvino
assert detector_config.device == "GPU"
assert detector_config.model.path == "/etc/hosts"
@patch("frigate.detectors.detector_config.load_labels")
def test_model_default_paths_per_detector(self, mock_labels):
mock_labels.return_value = {}
for devices, expected in (
(["cpu"], "/cpu_model.tflite"),
(["edgetpu:pci:0"], "/edgetpu_model.tflite"),
(["openvino:CPU"], "/openvino-model/ssdlite_mobilenet_v2.xml"),
):
config = {"models": [{"devices": devices}]}
frigate_config = FrigateConfig(**(deep_merge(config, self.minimal)))
assert frigate_config.primary_model.path == expected
@patch("frigate.detectors.detector_config.load_labels")
def test_camera_picks_model_by_scene(self, mock_labels):
mock_labels.return_value = {}
config = {
"models": [
{"scene": "outdoor", "devices": ["cpu"], "width": 320},
{"scene": "indoor", "devices": ["openvino:CPU"], "width": 300},
],
"cameras": {
"back": {
"detect": {"scene": "outdoor"},
"ffmpeg": {
"inputs": [
{"path": "rtsp://10.0.0.1:554/video", "roles": ["detect"]},
]
},
},
"edgetpu": {
"type": "edgetpu",
"model_path": "/edgetpu_model.tflite",
},
"openvino": {
"type": "openvino",
"front": {
"detect": {"scene": "indoor"},
"ffmpeg": {
"inputs": [
{"path": "rtsp://10.0.0.2:554/video", "roles": ["detect"]},
]
},
},
},
# needs to be a file that will exist, doesn't matter what
"model": {"path": "/etc/hosts", "width": 512},
}
frigate_config = FrigateConfig(**(deep_merge(config, self.minimal)))
assert "cpu" in frigate_config.detectors.keys()
assert "edgetpu" in frigate_config.detectors.keys()
assert "openvino" in frigate_config.detectors.keys()
assert frigate_config.model_for_camera("back").scene == SceneEnum.outdoor
assert frigate_config.model_for_camera("front").scene == SceneEnum.indoor
assert frigate_config.model_for_camera("back").width == 320
assert frigate_config.model_for_camera("front").width == 300
assert frigate_config.detectors["cpu"].type == DetectorTypeEnum.cpu
assert frigate_config.detectors["edgetpu"].type == DetectorTypeEnum.edgetpu
assert frigate_config.detectors["openvino"].type == DetectorTypeEnum.openvino
@patch("frigate.detectors.detector_config.load_labels")
def test_camera_requires_a_scene_without_a_default(self, mock_labels):
mock_labels.return_value = {}
config = {
"models": [
{"scene": "outdoor", "devices": ["cpu"]},
{"scene": "indoor", "devices": ["openvino:CPU"]},
],
}
assert frigate_config.detectors["cpu"].num_threads == 3
assert frigate_config.detectors["edgetpu"].device is None
assert frigate_config.detectors["openvino"].device is None
with self.assertRaises(ValidationError):
FrigateConfig(**(deep_merge(config, self.minimal)))
assert frigate_config.model.path == "/etc/hosts"
assert frigate_config.detectors["cpu"].model.path == "/cpu_model.tflite"
assert frigate_config.detectors["edgetpu"].model.path == "/edgetpu_model.tflite"
assert frigate_config.detectors["openvino"].model.path == "/etc/hosts"
@patch("frigate.detectors.detector_config.load_labels")
def test_camera_scene_without_a_model_falls_back_to_all(self, mock_labels):
mock_labels.return_value = {}
config = {
"models": [{"devices": ["cpu"]}],
"cameras": {
"back": {
"detect": {"scene": "outdoor"},
"ffmpeg": {
"inputs": [
{"path": "rtsp://10.0.0.1:554/video", "roles": ["detect"]},
]
},
},
},
}
frigate_config = FrigateConfig(**(deep_merge(config, self.minimal)))
assert frigate_config.model_for_camera("back").scene == SceneEnum.all
@patch("frigate.detectors.detector_config.load_labels")
def test_model_for_camera_resolves_camera_added_after_parse(self, mock_labels):
mock_labels.return_value = {}
config = {
"models": [
{"devices": ["cpu"], "width": 320},
{"scene": "outdoor", "devices": ["openvino:CPU"], "width": 416},
],
}
frigate_config = FrigateConfig(**(deep_merge(deepcopy(config), self.minimal)))
# runtime camera adds (wizard, clone, debug replay) insert an already
# resolved camera into the shared config without re-running parse
added = deepcopy(self.minimal)
added["cameras"]["new_cam"] = {
"detect": {"height": 1080, "width": 1920, "fps": 5, "scene": "outdoor"},
"ffmpeg": {
"inputs": [
{"path": "rtsp://10.0.0.2:554/video", "roles": ["detect"]},
]
},
}
new_config = FrigateConfig(**(deep_merge(deepcopy(config), added)))
frigate_config.cameras["new_cam"] = new_config.cameras["new_cam"]
assert frigate_config.model_for_camera("new_cam").scene == SceneEnum.outdoor
assert frigate_config.model_for_camera("new_cam").width == 416
@patch("frigate.detectors.detector_config.load_labels")
def test_model_for_camera_unknown_camera_uses_default_model(self, mock_labels):
mock_labels.return_value = {}
config = {
"models": [
{"devices": ["cpu"], "width": 320},
{"scene": "outdoor", "devices": ["openvino:CPU"], "width": 416},
],
}
frigate_config = FrigateConfig(**(deep_merge(deepcopy(config), self.minimal)))
# a caller racing a runtime remove may still name the popped camera
assert frigate_config.model_for_camera("removed").scene == SceneEnum.all
@patch("frigate.detectors.detector_config.load_labels")
def test_camera_scene_without_a_model_or_a_default(self, mock_labels):
mock_labels.return_value = {}
config = {
"models": [{"scene": "indoor", "devices": ["cpu"]}],
"cameras": {
"back": {
"detect": {"scene": "outdoor"},
"ffmpeg": {
"inputs": [
{"path": "rtsp://10.0.0.1:554/video", "roles": ["detect"]},
]
},
},
},
}
with self.assertRaises(ValidationError):
FrigateConfig(**(deep_merge(config, self.minimal)))
@patch("frigate.detectors.detector_config.load_labels")
def test_models_must_use_unique_scenes(self, mock_labels):
mock_labels.return_value = {}
config = {
"models": [
{"scene": "outdoor", "devices": ["cpu"]},
{"scene": "outdoor", "devices": ["openvino:CPU"]},
],
}
with self.assertRaises(ValidationError):
FrigateConfig(**(deep_merge(config, self.minimal)))
@patch("frigate.detectors.detector_config.load_labels")
def test_model_devices_must_share_a_detector(self, mock_labels):
mock_labels.return_value = {}
config = {"models": [{"devices": ["cpu", "openvino:CPU"]}]}
with self.assertRaises(ValidationError):
FrigateConfig(**(deep_merge(config, self.minimal)))
@patch("frigate.detectors.detector_config.load_labels")
def test_model_requires_a_known_detector(self, mock_labels):
mock_labels.return_value = {}
config = {"models": [{"devices": ["not_a_detector:0"]}]}
with self.assertRaises(ValidationError):
FrigateConfig(**(deep_merge(config, self.minimal)))
@patch("frigate.detectors.detector_config.load_labels")
def test_model_requires_a_device(self, mock_labels):
mock_labels.return_value = {}
config = {"models": [{"devices": []}]}
with self.assertRaises(ValidationError):
FrigateConfig(**(deep_merge(config, self.minimal)))
@patch("frigate.detectors.detector_config.load_labels")
def test_shareable_devices_may_repeat(self, mock_labels):
mock_labels.return_value = {}
config = {"models": [{"devices": ["openvino:GPU", "openvino:GPU"]}]}
frigate_config = FrigateConfig(**(deep_merge(config, self.minimal)))
devices = frigate_config.devices_for_model(frigate_config.primary_model)
assert runner_names(devices) == ["openvino:GPU", "openvino:GPU#2"]
@patch("frigate.detectors.detector_config.load_labels")
def test_exclusive_devices_may_not_repeat(self, mock_labels):
mock_labels.return_value = {}
config = {"models": [{"devices": ["edgetpu:pci:0", "edgetpu:pci:0"]}]}
with self.assertRaises(ValidationError):
FrigateConfig(**(deep_merge(config, self.minimal)))
def test_invalid_mqtt_config(self):
config = {
@@ -170,7 +360,7 @@ class TestConfig(unittest.TestCase):
def test_override_birdseye(self):
config = {
"mqtt": {"host": "mqtt"},
"birdseye": {"enabled": True, "mode": "continuous"},
"birdseye": {"enabled": True, "modes": ["continuous"]},
"cameras": {
"back": {
"ffmpeg": {
@@ -183,19 +373,28 @@ class TestConfig(unittest.TestCase):
"width": 1920,
"fps": 5,
},
"birdseye": {"enabled": False, "mode": "motion"},
"birdseye": {
"enabled": False,
"modes": ["motion"],
},
}
},
}
frigate_config = FrigateConfig(**config)
assert not frigate_config.cameras["back"].birdseye.enabled
assert frigate_config.cameras["back"].birdseye.mode is BirdseyeModeEnum.motion
assert frigate_config.cameras["back"].birdseye.modes == [
BirdseyeModeEnum.motion
]
def test_override_birdseye_non_inheritable(self):
config = {
"mqtt": {"host": "mqtt"},
"birdseye": {"enabled": True, "mode": "continuous", "height": 1920},
"birdseye": {
"enabled": True,
"modes": ["continuous"],
"height": 1920,
},
"cameras": {
"back": {
"ffmpeg": {
@@ -217,29 +416,38 @@ class TestConfig(unittest.TestCase):
def test_inherit_birdseye(self):
config = {
"mqtt": {"host": "mqtt"},
"birdseye": {"enabled": True, "mode": "continuous"},
"cameras": {
"back": {
"ffmpeg": {
"inputs": [
{"path": "rtsp://10.0.0.1:554/video", "roles": ["detect"]}
]
},
"detect": {
"height": 1080,
"width": 1920,
"fps": 5,
},
}
},
**self.minimal,
"birdseye": {"enabled": True, "modes": ["continuous"]},
}
frigate_config = FrigateConfig(**config)
assert frigate_config.cameras["back"].birdseye.enabled
assert (
frigate_config.cameras["back"].birdseye.mode is BirdseyeModeEnum.continuous
)
assert frigate_config.cameras["back"].birdseye.modes == [
BirdseyeModeEnum.continuous
]
def test_camera_modes_replace_the_global_list(self):
"""A camera list fully replaces the global one, it does not merge into it."""
config = {
**self.minimal,
"birdseye": {"modes": ["motion", "all_objects"]},
}
config["cameras"]["back"]["birdseye"] = {"modes": ["alerts"]}
frigate_config = FrigateConfig(**config)
assert frigate_config.cameras["back"].birdseye.modes == [
BirdseyeModeEnum.alerts
]
def test_camera_can_select_no_modes(self):
config = {
**self.minimal,
"birdseye": {"modes": ["motion"]},
}
config["cameras"]["back"]["birdseye"] = {"modes": []}
frigate_config = FrigateConfig(**config)
assert frigate_config.cameras["back"].birdseye.modes == []
def test_override_tracked_objects(self):
config = {
@@ -877,6 +1085,162 @@ class TestConfig(unittest.TestCase):
assert len(ffmpeg_cmds) == 1
assert "clips" not in ffmpeg_cmds[0]["roles"]
def test_record_sub_cmd_writes_sub_cache_path(self):
config = {
"mqtt": {"host": "mqtt"},
"cameras": {
"back": {
"ffmpeg": {
"inputs": [
{
"path": "rtsp://10.0.0.1:554/video",
"roles": ["detect", "record"],
},
{
"path": "rtsp://10.0.0.1:554/video2",
"roles": ["record_sub"],
},
]
},
"record": {"enabled": True, "sub": {"enabled": True}},
}
},
}
frigate_config = FrigateConfig(**config)
cmds = frigate_config.cameras["back"].ffmpeg_cmds
sub_cmds = [c for c in cmds if "record_sub" in c["roles"]]
assert len(sub_cmds) == 1
joined = " ".join(sub_cmds[0]["cmd"])
assert "back@sub@" in joined
def test_record_sub_disabled_no_sub_cache_path(self):
config = {
"mqtt": {"host": "mqtt"},
"cameras": {
"back": {
"ffmpeg": {
"inputs": [
{
"path": "rtsp://10.0.0.1:554/video",
"roles": ["detect", "record"],
},
]
},
"record": {"enabled": True, "sub": {"enabled": False}},
}
},
}
frigate_config = FrigateConfig(**config)
cmds = frigate_config.cameras["back"].ffmpeg_cmds
assert all("@sub@" not in " ".join(c["cmd"]) for c in cmds)
def _sub_record_config(self, ffmpeg_extra: dict | None = None) -> dict:
return {
"mqtt": {"host": "mqtt"},
"cameras": {
"back": {
"ffmpeg": {
"inputs": [
{
"path": "rtsp://10.0.0.1:554/video",
"roles": ["detect", "record"],
},
{
"path": "rtsp://10.0.0.1:554/video2",
"roles": ["record_sub"],
},
],
**(ffmpeg_extra or {}),
},
"record": {"enabled": True, "sub": {"enabled": True}},
}
},
}
def _sub_record_cmd(self, config: dict) -> str:
cmds = FrigateConfig(**config).cameras["back"].ffmpeg_cmds
sub_cmds = [c for c in cmds if "record_sub" in c["roles"]]
assert len(sub_cmds) == 1
return " ".join(sub_cmds[0]["cmd"])
def test_record_sub_output_args_inherit_record(self):
config = self._sub_record_config(
{"output_args": {"record": "preset-record-generic-audio-copy"}}
)
cmd = self._sub_record_cmd(config)
# the customized record args, not the stock aac default
assert "-c copy" in cmd
assert "-c:a aac" not in cmd
def test_record_sub_output_args_override_record(self):
config = self._sub_record_config(
{
"output_args": {
"record": "preset-record-generic-audio-aac",
"record_sub": "preset-record-generic",
}
}
)
cmd = self._sub_record_cmd(config)
assert "-c copy -an" in cmd
assert "-c:a aac" not in cmd
def test_record_output_args_unaffected_by_record_sub(self):
config = self._sub_record_config(
{
"output_args": {
"record": "preset-record-generic-audio-aac",
"record_sub": "preset-record-generic",
}
}
)
cmds = FrigateConfig(**config).cameras["back"].ffmpeg_cmds
record_cmd = " ".join(next(c for c in cmds if "record" in c["roles"])["cmd"])
assert "-c:a aac" in record_cmd
def test_record_sub_manual_output_args(self):
config = self._sub_record_config(
{
"output_args": {
"record_sub": "-f segment -segment_time 10 -segment_format mp4 -reset_timestamps 1 -strftime 1 -c:v copy -c:a aac -ar 16000"
}
}
)
assert "-ar 16000" in self._sub_record_cmd(config)
def test_fails_on_bad_record_sub_segment_time(self):
config = self._sub_record_config(
{
"output_args": {
"record_sub": "-f segment -segment_time 70 -segment_format mp4 -reset_timestamps 1 -strftime 1 -c copy -an"
}
}
)
self.assertRaisesRegex(
ValueError,
"segment_time",
lambda: FrigateConfig(**config).cameras,
)
def test_record_sub_segment_time_not_checked_when_disabled(self):
config = self._sub_record_config(
{
"output_args": {
"record_sub": "-f segment -segment_time 70 -segment_format mp4 -reset_timestamps 1 -strftime 1 -c copy -an"
}
}
)
config["cameras"]["back"]["record"]["sub"]["enabled"] = False
FrigateConfig(**config).cameras
def test_max_disappeared_default(self):
config = {
"mqtt": {"host": "mqtt"},
@@ -956,7 +1320,7 @@ class TestConfig(unittest.TestCase):
def test_merge_labelmap(self):
config = {
"mqtt": {"host": "mqtt"},
"model": {"labelmap": {7: "truck"}},
"models": [{"labelmap": {7: "truck"}, "devices": ["cpu"]}],
"cameras": {
"back": {
"ffmpeg": {
@@ -977,7 +1341,29 @@ class TestConfig(unittest.TestCase):
}
frigate_config = FrigateConfig(**config)
assert frigate_config.model.merged_labelmap[7] == "truck"
assert frigate_config.primary_model.merged_labelmap[7] == "truck"
def test_audio_labelmap_inheritance_is_separate_from_model_labelmap(self):
config = deep_merge(
{
"audio": {"labelmap": {69: "dogs", 70: "dogs"}},
"cameras": {
"back": {
"audio": {"labelmap": {75: "dogs"}},
}
},
},
self.minimal,
)
frigate_config = FrigateConfig(**config)
assert frigate_config.cameras["back"].audio.labelmap == {
69: "dogs",
70: "dogs",
75: "dogs",
}
assert frigate_config.primary_model.merged_labelmap[69] != "dogs"
def test_default_labelmap_empty(self):
config = {
@@ -1002,12 +1388,12 @@ class TestConfig(unittest.TestCase):
}
frigate_config = FrigateConfig(**config)
assert frigate_config.model.merged_labelmap[0] == "person"
assert frigate_config.primary_model.merged_labelmap[0] == "person"
def test_default_labelmap(self):
config = {
"mqtt": {"host": "mqtt"},
"model": {"width": 320, "height": 320},
"models": [{"width": 320, "height": 320, "devices": ["cpu"]}],
"cameras": {
"back": {
"ffmpeg": {
@@ -1028,7 +1414,7 @@ class TestConfig(unittest.TestCase):
}
frigate_config = FrigateConfig(**config)
assert frigate_config.model.merged_labelmap[0] == "person"
assert frigate_config.primary_model.merged_labelmap[0] == "person"
def test_plus_labelmap(self):
with open(os.path.join(MODEL_CACHE_DIR, "test"), "w") as f:
@@ -1038,8 +1424,7 @@ class TestConfig(unittest.TestCase):
config = {
"mqtt": {"host": "mqtt"},
"detectors": {"cpu": {"type": "cpu"}},
"model": {"path": "plus://test"},
"models": [{"path": "plus://test", "devices": ["cpu"]}],
"cameras": {
"back": {
"ffmpeg": {
@@ -1060,7 +1445,7 @@ class TestConfig(unittest.TestCase):
}
frigate_config = FrigateConfig(**config)
assert frigate_config.model.merged_labelmap[0] == "amazon"
assert frigate_config.primary_model.merged_labelmap[0] == "amazon"
def test_fails_on_invalid_role(self):
config = {
@@ -1119,6 +1504,44 @@ class TestConfig(unittest.TestCase):
self.assertRaises(ValueError, lambda: FrigateConfig(**config))
def test_record_sub_config_defaults(self):
config = FrigateConfig(**self.minimal)
record = config.cameras["back"].record
assert record.sub.enabled is False
assert record.sub.continuous.days == 0
assert record.sub.alerts.mode == RetainModeEnum.motion
def test_record_sub_enabled_requires_role(self):
config = deepcopy(self.minimal)
config["cameras"]["back"]["ffmpeg"]["inputs"] = [
{"path": "rtsp://10.0.0.1:554/video", "roles": ["detect", "record"]},
]
config["cameras"]["back"]["record"] = {
"enabled": True,
"sub": {"enabled": True},
}
# no record_sub role assigned -> must raise
self.assertRaisesRegex(
ValueError,
"record_sub is not assigned",
lambda: FrigateConfig(**config),
)
def test_record_sub_role_accepted(self):
config = deepcopy(self.minimal)
config["cameras"]["back"]["ffmpeg"]["inputs"] = [
{"path": "rtsp://10.0.0.1:554/video", "roles": ["detect", "record"]},
{"path": "rtsp://10.0.0.1:554/video2", "roles": ["record_sub"]},
]
config["cameras"]["back"]["record"] = {
"enabled": True,
"sub": {"enabled": True, "continuous": {"days": 30}},
}
parsed = FrigateConfig(**config)
assert parsed.cameras["back"].record.sub.continuous.days == 30
def test_works_on_missing_role_multiple_cams(self):
config = {
"mqtt": {"host": "mqtt"},
+225
View File
@@ -0,0 +1,225 @@
"""Tests for migrating detectors and model into the models list."""
import logging
import os
import tempfile
import unittest
from unittest.mock import patch
from ruamel.yaml import YAML
from frigate.util.config import (
CURRENT_CONFIG_VERSION,
migrate_frigate_config,
migrate_models,
)
class TestMigrateModels(unittest.TestCase):
def test_single_cpu_detector(self):
migrated = migrate_models({"detectors": {"cpu": {"type": "cpu"}}})
self.assertEqual(migrated["models"], [{"scene": "all", "devices": ["cpu"]}])
self.assertNotIn("detectors", migrated)
def test_model_settings_are_carried_over(self):
migrated = migrate_models(
{
"detectors": {"coral": {"type": "edgetpu", "device": "pci:0"}},
"model": {"path": "plus://abc", "width": 320},
}
)
self.assertEqual(
migrated["models"],
[
{
"scene": "all",
"path": "plus://abc",
"width": 320,
"devices": ["edgetpu:pci:0"],
}
],
)
self.assertNotIn("model", migrated)
def test_multiple_corals_become_multiple_devices(self):
migrated = migrate_models(
{
"detectors": {
"coral1": {"type": "edgetpu", "device": "pci:0"},
"coral2": {"type": "edgetpu", "device": "pci:1"},
}
}
)
self.assertEqual(
migrated["models"][0]["devices"], ["edgetpu:pci:0", "edgetpu:pci:1"]
)
def test_several_detectors_on_one_device_stay_separate(self):
# a repeated device is now what running two inference processes on one
# piece of hardware looks like
migrated = migrate_models(
{
"detectors": {
"ov_0": {"type": "openvino", "device": "GPU"},
"ov_1": {"type": "openvino", "device": "GPU"},
}
}
)
self.assertEqual(
migrated["models"][0]["devices"], ["openvino:GPU", "openvino:GPU"]
)
def test_repeated_exclusive_devices_are_collapsed(self):
# two detectors both grabbing the first TPU was never really two TPUs
migrated = migrate_models(
{
"detectors": {
"coral_0": {"type": "edgetpu", "device": "usb"},
"coral_1": {"type": "edgetpu", "device": "usb"},
}
}
)
self.assertEqual(migrated["models"][0]["devices"], ["edgetpu:usb"])
def test_detectors_that_named_the_device_field_differently(self):
migrated = migrate_models(
{
"detectors": {
"rk": {"type": "rknn", "num_cores": 2},
}
}
)
self.assertEqual(migrated["models"][0]["devices"], ["rknn:2"])
def test_empty_edgetpu_device_is_kept(self):
# an empty device selects a native Coral, which is not the same as
# letting the delegate pick
migrated = migrate_models(
{"detectors": {"coral": {"type": "edgetpu", "device": ""}}}
)
self.assertEqual(migrated["models"][0]["devices"], ["edgetpu:"])
def test_model_path_overrides_the_model(self):
migrated = migrate_models(
{
"detectors": {
"coral": {"type": "edgetpu", "model_path": "/custom.tflite"}
},
"model": {"path": "/ignored.tflite", "width": 320},
}
)
self.assertEqual(migrated["models"][0]["path"], "/custom.tflite")
def test_no_detectors_falls_back_to_cpu(self):
migrated = migrate_models({"model": {"width": 320}})
self.assertEqual(migrated["models"][0]["devices"], ["cpu"])
def test_dropped_remote_detector_options_are_logged(self):
with self.assertLogs("frigate.util.config", level=logging.ERROR) as logs:
migrated = migrate_models(
{
"detectors": {
"ds": {
"type": "deepstack",
"api_url": "http://host:5000/v1/vision/detection",
"api_key": "secret",
}
}
}
)
self.assertEqual(
migrated["models"][0]["devices"],
["deepstack:http://host:5000/v1/vision/detection"],
)
self.assertTrue(any("api_key" in message for message in logs.output))
def test_mixed_detector_types_are_logged(self):
with self.assertLogs("frigate.util.config", level=logging.ERROR) as logs:
migrate_models(
{
"detectors": {
"ov": {"type": "openvino", "device": "GPU"},
"coral": {"type": "edgetpu", "device": "pci:0"},
}
}
)
self.assertTrue(any("more than one type" in message for message in logs.output))
def test_other_keys_are_untouched(self):
migrated = migrate_models(
{"mqtt": {"host": "mqtt"}, "detectors": {"cpu": {"type": "cpu"}}}
)
self.assertEqual(migrated["mqtt"], {"host": "mqtt"})
class TestMigrateConfigFile(unittest.TestCase):
"""The full file migration, which is gated on shape as well as version."""
def setUp(self):
self.temp_dir = tempfile.TemporaryDirectory()
self.addCleanup(self.temp_dir.cleanup)
self.config_file = os.path.join(self.temp_dir.name, "config.yml")
patcher = patch("frigate.util.config.CONFIG_DIR", self.temp_dir.name)
patcher.start()
self.addCleanup(patcher.stop)
def _migrate(self, config: str) -> dict:
with open(self.config_file, "w") as f:
f.write(config)
migrate_frigate_config(self.config_file)
with open(self.config_file) as f:
return YAML().load(f)
def test_migrates_a_config_already_stamped_with_the_current_version(self):
# 0.19 is unreleased, so a dev config can be current and still use
# the pre-models keys
migrated = self._migrate(
"mqtt:\n"
" enabled: false\n"
"detectors:\n"
" ov:\n"
" type: openvino\n"
" device: GPU\n"
"cameras: {}\n"
f"version: {CURRENT_CONFIG_VERSION}\n"
)
self.assertEqual(migrated["models"][0]["devices"], ["openvino:GPU"])
self.assertNotIn("detectors", migrated)
def test_a_migrated_config_is_left_alone(self):
migrated = self._migrate(
"mqtt:\n"
" enabled: false\n"
"models:\n"
" - scene: all\n"
" devices:\n"
" - openvino:GPU\n"
"cameras: {}\n"
f"version: {CURRENT_CONFIG_VERSION}\n"
)
self.assertEqual(
migrated["models"], [{"scene": "all", "devices": ["openvino:GPU"]}]
)
self.assertFalse(
os.path.exists(os.path.join(self.temp_dir.name, "backup_config.yaml"))
)
if __name__ == "__main__":
unittest.main(verbosity=2)

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