Files
blakeblackshear.frigate/frigate/track/object_processing.py
Nicolas Mowen d24b96d3bb Early 0.18 work (#22138)
* Update version

* Create scaffolding for case management (#21293)

* implement case management for export apis (#21295)

* refactor vainfo to search for first GPU (#21296)

use existing LibvaGpuSelector to pick appropritate libva device

* Case management UI (#21299)

* Refactor export cards to match existing cards in other UI pages

* Show cases separately from exports

* Add proper filtering and display of cases

* Add ability to edit and select cases for exports

* Cleanup typing

* Hide if no unassigned

* Cleanup hiding logic

* fix scrolling

* Improve layout

* Camera connection quality indicator (#21297)

* add camera connection quality metrics and indicator

* formatting

* move stall calcs to watchdog

* clean up

* change watchdog to 1s and separately track time for ffmpeg retry_interval

* implement status caching to reduce message volume

* Export filter UI (#21322)

* Get started on export filters

* implement basic filter

* Implement filtering and adjust api

* Improve filter handling

* Improve navigation

* Cleanup

* handle scrolling

* Refactor temperature reporting for detectors and implement Hailo temp reading (#21395)

* Add Hailo temperature retrieval

* Refactor `get_hailo_temps()` to use ctxmanager

* Show Hailo temps in system UI

* Move hailo_platform import to get_hailo_temps

* Refactor temperatures calculations to use within detector block

* Adjust webUI to handle new location

---------

Co-authored-by: tigattack <10629864+tigattack@users.noreply.github.com>

* Camera-specific hwaccel settings for timelapse exports (correct base) (#21386)

* added hwaccel_args to camera.record.export config struct

* populate camera.record.export.hwaccel_args with a cascade up to camera then global if 'auto'

* use new hwaccel args in export

* added documentation for camera-specific hwaccel export

* fix c/p error

* missed an import

* fleshed out the docs and comments a bit

* ruff lint

* separated out the tips in the doc

* fix documentation

* fix and simplify reference config doc

* Add support for GPU and NPU temperatures (#21495)

* Add rockchip temps

* Add support for GPU and NPU temperatures in the frontend

* Add support for Nvidia temperature

* Improve separation

* Adjust graph scaling

* Exports Improvements (#21521)

* Add images to case folder view

* Add ability to select case in export dialog

* Add to mobile review too

* Add API to handle deleting recordings  (#21520)

* Add recording delete API

* Re-organize recordings apis

* Fix import

* Consolidate query types

* Add media sync API endpoint (#21526)

* add media cleanup functions

* add endpoint

* remove scheduled sync recordings from cleanup

* move to utils dir

* tweak import

* remove sync_recordings and add config migrator

* remove sync_recordings

* docs

* remove key

* clean up docs

* docs fix

* docs tweak

* Media sync API refactor and UI (#21542)

* generic job infrastructure

* types and dispatcher changes for jobs

* save data in memory only for completed jobs

* implement media sync job and endpoints

* change logs to debug

* websocket hook and types

* frontend

* i18n

* docs tweaks

* endpoint descriptions

* tweak docs

* use same logging pattern in sync_recordings as the other sync functions (#21625)

* Fix incorrect counting in sync_recordings (#21626)

* Update go2rtc to v1.9.13 (#21648)

Co-authored-by: Eugeny Tulupov <eugeny.tulupov@spirent.com>

* Refactor Time-Lapse Export (#21668)

* refactor time lapse creation to be a separate API call with ability to pass arbitrary ffmpeg args

* Add CPU fallback

* Optimize empty directory cleanup for recordings (#21695)

The previous empty directory cleanup did a full recursive directory
walk, which can be extremely slow. This new implementation only removes
directories which have a chance of being empty due to a recent file
deletion.

* Implement llama.cpp GenAI Provider (#21690)

* Implement llama.cpp GenAI Provider

* Add docs

* Update links

* Fix broken mqtt links

* Fix more broken anchors

* Remove parents in remove_empty_directories (#21726)

The original implementation did a full directory tree walk to find and remove
empty directories, so this implementation should remove the parents as well,
like the original did.

* Implement LLM Chat API with tool calling support (#21731)

* Implement initial tools definiton APIs

* Add initial chat completion API with tool support

* Implement other providers

* Cleanup

* Offline preview image (#21752)

* use latest preview frame for latest image when camera is offline

* remove frame extraction logic

* tests

* frontend

* add description to api endpoint

* Update to ROCm 7.2.0 (#21753)

* Update to ROCm 7.2.0

* ROCm now works properly with JinaV1

* Arcface has compilation error

* Add live context tool to LLM (#21754)

* Add live context tool

* Improve handling of images in request

* Improve prompt caching

* Add networking options for configuring listening ports (#21779)

* feat: add X-Frame-Time when returning snapshot (#21932)

Co-authored-by: Florent MORICONI <170678386+fmcloudconsulting@users.noreply.github.com>

* Improve jsmpeg player websocket handling (#21943)

* improve jsmpeg player websocket handling

prevent websocket console messages from appearing when player is destroyed

* reformat files after ruff upgrade

* Allow API Events to be Detections or Alerts, depending on the Event Label (#21923)

* - API created events will be alerts OR detections, depending on the event label, defaulting to alerts
- Indefinite API events will extend the recording segment until those events are ended
- API event start time is the actual start time, instead of having a pre-buffer of record.event_pre_capture

* Instead of checking for indefinite events on a camera before deciding if we should end the segment, only update last_detection_time and last_alert_time if frame_time is greater, which should have the same effect

* Add the ability to set a pre_capture number of seconds when creating a manual event via the API. Default behavior unchanged

* Remove unnecessary _publish_segment_start() call

* Formatting

* handle last_alert_time or last_detection_time being None when checking them against the frame_time

* comment manual_info["label"].split(": ")[0] for clarity

* ffmpeg Preview Segment Optimization for "high" and "very_high" (#21996)

* Introduce qmax parameter for ffmpeg preview encoding

Added PREVIEW_QMAX_PARAM to control ffmpeg encoding quality.

* formatting

* Fix spacing in qmax parameters for preview quality

* Adapt to new Gemini format

* Fix frame time access

* Remove exceptions

* Cleanup

---------

Co-authored-by: Josh Hawkins <32435876+hawkeye217@users.noreply.github.com>
Co-authored-by: tigattack <10629864+tigattack@users.noreply.github.com>
Co-authored-by: Andrew Roberts <adroberts@gmail.com>
Co-authored-by: Eugeny Tulupov <zhekka3@gmail.com>
Co-authored-by: Eugeny Tulupov <eugeny.tulupov@spirent.com>
Co-authored-by: John Shaw <1753078+johnshaw@users.noreply.github.com>
Co-authored-by: Eric Work <work.eric@gmail.com>
Co-authored-by: FL42 <46161216+fl42@users.noreply.github.com>
Co-authored-by: Florent MORICONI <170678386+fmcloudconsulting@users.noreply.github.com>
Co-authored-by: nulledy <254504350+nulledy@users.noreply.github.com>
2026-02-26 21:16:10 -07:00

808 lines
28 KiB
Python

import base64
import datetime
import json
import logging
import queue
import threading
from collections import defaultdict
from enum import Enum
from multiprocessing import Queue as MpQueue
from multiprocessing.synchronize import Event as MpEvent
from typing import Any
import cv2
import numpy as np
from peewee import SQL, DoesNotExist
from frigate.camera.state import CameraState
from frigate.comms.detections_updater import DetectionPublisher, DetectionTypeEnum
from frigate.comms.dispatcher import Dispatcher
from frigate.comms.event_metadata_updater import (
EventMetadataSubscriber,
EventMetadataTypeEnum,
)
from frigate.comms.events_updater import EventEndSubscriber, EventUpdatePublisher
from frigate.comms.inter_process import InterProcessRequestor
from frigate.config import (
CameraMqttConfig,
FrigateConfig,
RecordConfig,
SnapshotsConfig,
)
from frigate.config.camera.updater import (
CameraConfigUpdateEnum,
CameraConfigUpdateSubscriber,
)
from frigate.const import (
FAST_QUEUE_TIMEOUT,
UPDATE_CAMERA_ACTIVITY,
UPSERT_REVIEW_SEGMENT,
)
from frigate.events.types import EventStateEnum, EventTypeEnum
from frigate.models import Event, ReviewSegment, Timeline
from frigate.ptz.autotrack import PtzAutoTrackerThread
from frigate.track.tracked_object import TrackedObject
from frigate.util.image import SharedMemoryFrameManager
logger = logging.getLogger(__name__)
class ManualEventState(str, Enum):
complete = "complete"
start = "start"
end = "end"
class TrackedObjectProcessor(threading.Thread):
def __init__(
self,
config: FrigateConfig,
dispatcher: Dispatcher,
tracked_objects_queue: MpQueue,
ptz_autotracker_thread: PtzAutoTrackerThread,
stop_event: MpEvent,
) -> None:
super().__init__(name="detected_frames_processor")
self.config = config
self.dispatcher = dispatcher
self.tracked_objects_queue = tracked_objects_queue
self.stop_event: MpEvent = stop_event
self.camera_states: dict[str, CameraState] = {}
self.frame_manager = SharedMemoryFrameManager()
self.last_motion_detected: dict[str, float] = {}
self.ptz_autotracker_thread = ptz_autotracker_thread
self.camera_config_subscriber = CameraConfigUpdateSubscriber(
self.config,
self.config.cameras,
[
CameraConfigUpdateEnum.add,
CameraConfigUpdateEnum.enabled,
CameraConfigUpdateEnum.motion,
CameraConfigUpdateEnum.objects,
CameraConfigUpdateEnum.remove,
CameraConfigUpdateEnum.zones,
],
)
self.requestor = InterProcessRequestor()
self.detection_publisher = DetectionPublisher(DetectionTypeEnum.all.value)
self.event_sender = EventUpdatePublisher()
self.event_end_subscriber = EventEndSubscriber()
self.sub_label_subscriber = EventMetadataSubscriber(EventMetadataTypeEnum.all)
self.camera_activity: dict[str, dict[str, Any]] = {}
self.ongoing_manual_events: dict[str, str] = {}
# {
# 'zone_name': {
# 'person': {
# 'camera_1': 2,
# 'camera_2': 1
# }
# }
# }
self.zone_data: dict[str, dict[str, Any]] = defaultdict(
lambda: defaultdict(dict)
)
self.active_zone_data: dict[str, dict[str, Any]] = defaultdict(
lambda: defaultdict(dict)
)
for camera in self.config.cameras.keys():
self.create_camera_state(camera)
def create_camera_state(self, camera: str) -> None:
"""Creates a new camera state."""
def start(camera: str, obj: TrackedObject, frame_name: str) -> None:
self.event_sender.publish(
(
EventTypeEnum.tracked_object,
EventStateEnum.start,
camera,
frame_name,
obj.to_dict(),
)
)
def update(camera: str, obj: TrackedObject, frame_name: str) -> None:
obj.has_snapshot = self.should_save_snapshot(camera, obj)
obj.has_clip = self.should_retain_recording(camera, obj)
after = obj.to_dict()
message = {
"before": obj.previous,
"after": after,
"type": "new" if obj.previous["false_positive"] else "update",
}
self.dispatcher.publish("events", json.dumps(message), retain=False)
obj.previous = after
self.event_sender.publish(
(
EventTypeEnum.tracked_object,
EventStateEnum.update,
camera,
frame_name,
obj.to_dict(),
)
)
def autotrack(camera: str, obj: TrackedObject, frame_name: str) -> None:
self.ptz_autotracker_thread.ptz_autotracker.autotrack_object(camera, obj)
def end(camera: str, obj: TrackedObject, frame_name: str) -> None:
# populate has_snapshot
obj.has_snapshot = self.should_save_snapshot(camera, obj)
obj.has_clip = self.should_retain_recording(camera, obj)
# write thumbnail to disk if it will be saved as an event
if obj.has_snapshot or obj.has_clip:
obj.write_thumbnail_to_disk()
# write the snapshot to disk
if obj.has_snapshot:
obj.write_snapshot_to_disk()
if not obj.false_positive:
message = {
"before": obj.previous,
"after": obj.to_dict(),
"type": "end",
}
self.dispatcher.publish("events", json.dumps(message), retain=False)
self.ptz_autotracker_thread.ptz_autotracker.end_object(camera, obj)
self.event_sender.publish(
(
EventTypeEnum.tracked_object,
EventStateEnum.end,
camera,
frame_name,
obj.to_dict(),
)
)
def snapshot(camera: str, obj: TrackedObject) -> bool:
mqtt_config: CameraMqttConfig = self.config.cameras[camera].mqtt
if mqtt_config.enabled and self.should_mqtt_snapshot(camera, obj):
jpg_bytes, _ = obj.get_img_bytes(
ext="jpg",
timestamp=mqtt_config.timestamp,
bounding_box=mqtt_config.bounding_box,
crop=mqtt_config.crop,
height=mqtt_config.height,
quality=mqtt_config.quality,
)
if jpg_bytes is None:
logger.warning(
f"Unable to send mqtt snapshot for {obj.obj_data['id']}."
)
else:
self.dispatcher.publish(
f"{camera}/{obj.obj_data['label']}/snapshot",
jpg_bytes,
retain=True,
)
if obj.obj_data.get("sub_label"):
sub_label = obj.obj_data["sub_label"][0]
if sub_label in self.config.model.all_attribute_logos:
self.dispatcher.publish(
f"{camera}/{sub_label}/snapshot",
jpg_bytes,
retain=True,
)
return True
return False
def camera_activity(camera: str, activity: dict[str, Any]) -> None:
last_activity = self.camera_activity.get(camera)
if not last_activity or activity != last_activity:
self.camera_activity[camera] = activity
self.requestor.send_data(UPDATE_CAMERA_ACTIVITY, self.camera_activity)
camera_state = CameraState(
camera, self.config, self.frame_manager, self.ptz_autotracker_thread
)
camera_state.on("start", start)
camera_state.on("autotrack", autotrack)
camera_state.on("update", update)
camera_state.on("end", end)
camera_state.on("snapshot", snapshot)
camera_state.on("camera_activity", camera_activity)
self.camera_states[camera] = camera_state
def should_save_snapshot(self, camera: str, obj: TrackedObject) -> bool:
if obj.false_positive:
return False
snapshot_config: SnapshotsConfig = self.config.cameras[camera].snapshots
if not snapshot_config.enabled:
return False
# object never changed position
if obj.obj_data["position_changes"] == 0:
return False
# if there are required zones and there is no overlap
required_zones = snapshot_config.required_zones
if len(required_zones) > 0 and not set(obj.entered_zones) & set(required_zones):
logger.debug(
f"Not creating snapshot for {obj.obj_data['id']} because it did not enter required zones"
)
return False
return True
def should_retain_recording(self, camera: str, obj: TrackedObject) -> bool:
if obj.false_positive:
return False
record_config: RecordConfig = self.config.cameras[camera].record
# Recording is disabled
if not record_config.enabled:
return False
# object never changed position
if obj.obj_data["position_changes"] == 0:
return False
# If the object is not considered an alert or detection
if obj.max_severity is None:
return False
return True
def should_mqtt_snapshot(self, camera: str, obj: TrackedObject) -> bool:
# object never changed position
if obj.is_stationary():
return False
# if there are required zones and there is no overlap
required_zones = self.config.cameras[camera].mqtt.required_zones
if len(required_zones) > 0 and not set(obj.entered_zones) & set(required_zones):
logger.debug(
f"Not sending mqtt for {obj.obj_data['id']} because it did not enter required zones"
)
return False
return True
def update_mqtt_motion(
self, camera: str, frame_time: float, motion_boxes: list
) -> None:
# publish if motion is currently being detected
if motion_boxes:
# only send ON if motion isn't already active
if self.last_motion_detected.get(camera, 0) == 0:
self.dispatcher.publish(
f"{camera}/motion",
"ON",
retain=False,
)
# always updated latest motion
self.last_motion_detected[camera] = frame_time
elif self.last_motion_detected.get(camera, 0) > 0:
mqtt_delay = self.config.cameras[camera].motion.mqtt_off_delay
# If no motion, make sure the off_delay has passed
if frame_time - self.last_motion_detected.get(camera, 0) >= mqtt_delay:
self.dispatcher.publish(
f"{camera}/motion",
"OFF",
retain=False,
)
# reset the last_motion so redundant `off` commands aren't sent
self.last_motion_detected[camera] = 0
def get_best(self, camera: str, label: str) -> dict[str, Any]:
# TODO: need a lock here
camera_state = self.camera_states[camera]
if label in camera_state.best_objects:
best_obj = camera_state.best_objects[label]
if not best_obj.thumbnail_data:
return {}
best = best_obj.thumbnail_data.copy()
best["frame"] = camera_state.frame_cache.get(
best_obj.thumbnail_data["frame_time"]
)
return best
else:
return {}
def get_current_frame(
self, camera: str, draw_options: dict[str, Any] = {}
) -> np.ndarray | None:
if camera == "birdseye":
return self.frame_manager.get(
"birdseye",
(self.config.birdseye.height * 3 // 2, self.config.birdseye.width),
)
if camera not in self.camera_states:
return None
return self.camera_states[camera].get_current_frame(draw_options)
def get_current_frame_time(self, camera: str) -> float:
"""Returns the latest frame time for a given camera."""
return self.camera_states[camera].current_frame_time
def set_sub_label(
self, event_id: str, sub_label: str | None, score: float | None
) -> None:
"""Update sub label for given event id."""
tracked_obj: TrackedObject | None = None
for state in self.camera_states.values():
tracked_obj = state.tracked_objects.get(event_id)
if tracked_obj is not None:
break
try:
event: Event | None = Event.get(Event.id == event_id)
except DoesNotExist:
event = None
if not tracked_obj and not event:
return
if tracked_obj:
tracked_obj.obj_data["sub_label"] = (sub_label, score)
if event:
event.sub_label = sub_label # type: ignore[assignment]
data = event.data
if sub_label is None:
data["sub_label_score"] = None # type: ignore[index]
elif score is not None:
data["sub_label_score"] = score # type: ignore[index]
event.data = data
event.save()
# update timeline items
Timeline.update(
data=Timeline.data.update({"sub_label": (sub_label, score)})
).where(Timeline.source_id == event_id).execute()
# only update ended review segments
# manually updating a sub_label from the UI is only possible for ended tracked objects
try:
review_segment = ReviewSegment.get(
(
SQL(
"json_extract(data, '$.detections') LIKE ?",
[f'%"{event_id}"%'],
)
)
& (ReviewSegment.end_time.is_null(False))
)
segment_data = review_segment.data
detection_ids = segment_data.get("detections", [])
# Rebuild objects list and sync sub_labels
objects_list = []
sub_labels = set()
events = Event.select(Event.id, Event.label, Event.sub_label).where(
Event.id.in_(detection_ids) # type: ignore[call-arg, misc]
)
for det_event in events:
if det_event.sub_label:
sub_labels.add(det_event.sub_label)
objects_list.append(
f"{det_event.label}-verified"
) # eg, "bird-verified"
else:
objects_list.append(det_event.label) # eg, "bird"
segment_data["sub_labels"] = list(sub_labels)
segment_data["objects"] = objects_list
updated_data = {
ReviewSegment.id.name: review_segment.id,
ReviewSegment.camera.name: review_segment.camera,
ReviewSegment.start_time.name: review_segment.start_time,
ReviewSegment.end_time.name: review_segment.end_time,
ReviewSegment.severity.name: review_segment.severity,
ReviewSegment.thumb_path.name: review_segment.thumb_path,
ReviewSegment.data.name: segment_data,
}
self.requestor.send_data(UPSERT_REVIEW_SEGMENT, updated_data)
logger.debug(
f"Updated sub_label for event {event_id} in review segment {review_segment.id}"
)
except DoesNotExist:
logger.debug(
f"No review segment found with event ID {event_id} when updating sub_label"
)
def set_object_attribute(
self,
event_id: str,
field_name: str,
field_value: str | None,
score: float | None,
) -> None:
"""Update attribute for given event id."""
tracked_obj: TrackedObject | None = None
for state in self.camera_states.values():
tracked_obj = state.tracked_objects.get(event_id)
if tracked_obj is not None:
break
try:
event: Event | None = Event.get(Event.id == event_id)
except DoesNotExist:
event = None
if not tracked_obj and not event:
return
if tracked_obj:
tracked_obj.obj_data[field_name] = (
field_value,
score,
)
if event:
data = event.data
data[field_name] = field_value # type: ignore[index]
if field_value is None:
data[f"{field_name}_score"] = None # type: ignore[index]
elif score is not None:
data[f"{field_name}_score"] = score # type: ignore[index]
event.data = data
event.save()
def save_lpr_snapshot(self, payload: tuple) -> None:
# save the snapshot image
(frame, event_id, camera) = payload
img = cv2.imdecode(
np.frombuffer(base64.b64decode(frame), dtype=np.uint8),
cv2.IMREAD_COLOR,
)
self.camera_states[camera].save_manual_event_image(
img, event_id, "license_plate", {}
)
def create_manual_event(self, payload: tuple) -> None:
(
frame_time,
camera_name,
label,
event_id,
include_recording,
score,
sub_label,
duration,
source_type,
draw,
pre_capture,
) = payload
# save the snapshot image
self.camera_states[camera_name].save_manual_event_image(
None, event_id, label, draw
)
end_time = frame_time + duration if duration is not None else None
start_time = (
frame_time - self.config.cameras[camera_name].record.event_pre_capture
if pre_capture is None
else frame_time - pre_capture
)
# send event to event maintainer
self.event_sender.publish(
(
EventTypeEnum.api,
EventStateEnum.start,
camera_name,
"",
{
"id": event_id,
"label": label,
"sub_label": sub_label,
"score": score,
"camera": camera_name,
"start_time": start_time,
"end_time": end_time,
"has_clip": self.config.cameras[camera_name].record.enabled
and include_recording,
"has_snapshot": True,
"type": source_type,
},
)
)
if source_type == "api":
self.ongoing_manual_events[event_id] = camera_name
self.detection_publisher.publish(
(
camera_name,
frame_time,
{
"state": (
ManualEventState.complete
if end_time
else ManualEventState.start
),
"label": f"{label}: {sub_label}" if sub_label else label,
"event_id": event_id,
"end_time": end_time,
},
),
DetectionTypeEnum.api.value,
)
def create_lpr_event(self, payload: tuple) -> None:
(
frame_time,
camera_name,
label,
event_id,
include_recording,
score,
sub_label,
plate,
) = payload
# send event to event maintainer
self.event_sender.publish(
(
EventTypeEnum.api,
EventStateEnum.start,
camera_name,
"",
{
"id": event_id,
"label": label,
"sub_label": sub_label,
"score": score,
"camera": camera_name,
"start_time": frame_time
- self.config.cameras[camera_name].record.event_pre_capture,
"end_time": None,
"has_clip": self.config.cameras[camera_name].record.enabled
and include_recording,
"has_snapshot": True,
"type": "api",
"recognized_license_plate": plate,
"recognized_license_plate_score": score,
},
)
)
self.ongoing_manual_events[event_id] = camera_name
self.detection_publisher.publish(
(
camera_name,
frame_time,
{
"state": ManualEventState.start,
"label": f"{label}: {sub_label}" if sub_label else label,
"event_id": event_id,
"end_time": None,
},
),
DetectionTypeEnum.lpr.value,
)
def end_manual_event(self, payload: tuple) -> None:
(event_id, end_time) = payload
self.event_sender.publish(
(
EventTypeEnum.api,
EventStateEnum.end,
None,
"",
{"id": event_id, "end_time": end_time},
)
)
if event_id in self.ongoing_manual_events:
self.detection_publisher.publish(
(
self.ongoing_manual_events[event_id],
end_time,
{
"state": ManualEventState.end,
"event_id": event_id,
"end_time": end_time,
},
),
DetectionTypeEnum.api.value,
)
self.ongoing_manual_events.pop(event_id)
def force_end_all_events(self, camera: str, camera_state: CameraState) -> None:
"""Ends all active events on camera when disabling."""
last_frame_name = camera_state.previous_frame_id
for obj_id, obj in list(camera_state.tracked_objects.items()):
if "end_time" not in obj.obj_data:
logger.debug(f"Camera {camera} disabled, ending active event {obj_id}")
obj.obj_data["end_time"] = datetime.datetime.now().timestamp()
# end callbacks
for callback in camera_state.callbacks["end"]:
callback(camera, obj, last_frame_name)
# camera activity callbacks
for callback in camera_state.callbacks["camera_activity"]:
callback(
camera,
{"enabled": False, "motion": 0, "objects": []},
)
def run(self) -> None:
while not self.stop_event.is_set():
# check for config updates
updated_topics = self.camera_config_subscriber.check_for_updates()
if "enabled" in updated_topics:
for camera in updated_topics["enabled"]:
if self.camera_states[camera].prev_enabled is None:
self.camera_states[camera].prev_enabled = self.config.cameras[
camera
].enabled
elif "add" in updated_topics:
for camera in updated_topics["add"]:
self.config.cameras[camera] = (
self.camera_config_subscriber.camera_configs[camera]
)
self.create_camera_state(camera)
elif "remove" in updated_topics:
for camera in updated_topics["remove"]:
camera_state = self.camera_states[camera]
camera_state.shutdown()
self.camera_states.pop(camera)
# manage camera disabled state
for camera, config in self.config.cameras.items():
if not config.enabled_in_config:
continue
current_enabled = config.enabled
camera_state = self.camera_states[camera]
if camera_state.prev_enabled and not current_enabled:
logger.debug(f"Not processing objects for disabled camera {camera}")
self.force_end_all_events(camera, camera_state)
camera_state.prev_enabled = current_enabled
if not current_enabled:
continue
# check for sub label updates
while True:
update = self.sub_label_subscriber.check_for_update(timeout=0)
if not update:
break
(raw_topic, payload) = update
if not raw_topic or not payload:
break
topic = str(raw_topic)
if topic.endswith(EventMetadataTypeEnum.sub_label.value):
(event_id, sub_label, score) = payload
self.set_sub_label(event_id, sub_label, score)
if topic.endswith(EventMetadataTypeEnum.attribute.value):
(event_id, field_name, field_value, score) = payload
self.set_object_attribute(event_id, field_name, field_value, score)
elif topic.endswith(EventMetadataTypeEnum.lpr_event_create.value):
self.create_lpr_event(payload)
elif topic.endswith(EventMetadataTypeEnum.save_lpr_snapshot.value):
self.save_lpr_snapshot(payload)
elif topic.endswith(EventMetadataTypeEnum.manual_event_create.value):
self.create_manual_event(payload)
elif topic.endswith(EventMetadataTypeEnum.manual_event_end.value):
self.end_manual_event(payload)
try:
(
camera,
frame_name,
frame_time,
current_tracked_objects,
motion_boxes,
regions,
) = self.tracked_objects_queue.get(True, 1)
except queue.Empty:
continue
if not self.config.cameras[camera].enabled:
logger.debug(f"Camera {camera} disabled, skipping update")
continue
camera_state = self.camera_states[camera]
camera_state.update(
frame_name, frame_time, current_tracked_objects, motion_boxes, regions
)
self.update_mqtt_motion(camera, frame_time, motion_boxes)
tracked_objects = [
o.to_dict() for o in camera_state.tracked_objects.values()
]
# publish info on this frame
self.detection_publisher.publish(
(
camera,
frame_name,
frame_time,
tracked_objects,
motion_boxes,
regions,
),
DetectionTypeEnum.video.value,
)
# cleanup event finished queue
while not self.stop_event.is_set():
update = self.event_end_subscriber.check_for_update(
timeout=FAST_QUEUE_TIMEOUT
)
if not update:
break
event_id, camera, _ = update
self.camera_states[camera].finished(event_id)
# shut down camera states
for state in self.camera_states.values():
state.shutdown()
self.requestor.stop()
self.detection_publisher.stop()
self.event_sender.stop()
self.event_end_subscriber.stop()
self.sub_label_subscriber.stop()
self.camera_config_subscriber.stop()
logger.info("Exiting object processor...")