frigate/frigate/timeline.py
Josh Hawkins aa8b423b68
Miscellaneous Fixes (#21024)
* fix wording in reference config

* spacing tweaks

* make live view settings drawer scrollable

* clarify audio transcription docs

* change audio transcription icon to activity indicator when transcription is in progress

the backend doesn't implement any kind of queueing for speech event transcription

* tracking details tweaks

- Add attribute box overlay and area
- Add score
- Throttle swr revalidation during video component rerendering

* add mse codecs to console debug on errors

* add camera name
2025-11-24 06:34:56 -07:00

198 lines
7.0 KiB
Python

"""Record events for object, audio, etc. detections."""
import logging
import queue
import threading
from multiprocessing import Queue
from multiprocessing.synchronize import Event as MpEvent
from typing import Any
from frigate.config import FrigateConfig
from frigate.events.maintainer import EventStateEnum, EventTypeEnum
from frigate.models import Timeline
from frigate.util.builtin import to_relative_box
logger = logging.getLogger(__name__)
class TimelineProcessor(threading.Thread):
"""Handle timeline queue and update DB."""
def __init__(
self,
config: FrigateConfig,
queue: Queue,
stop_event: MpEvent,
) -> None:
super().__init__(name="timeline_processor")
self.config = config
self.queue = queue
self.stop_event = stop_event
self.pre_event_cache: dict[str, list[dict[str, Any]]] = {}
def run(self) -> None:
while not self.stop_event.is_set():
try:
(
camera,
input_type,
event_type,
prev_event_data,
event_data,
) = self.queue.get(timeout=1)
except queue.Empty:
continue
if input_type == EventTypeEnum.tracked_object:
# None prev_event_data is only allowed for the start of an event
if event_type != EventStateEnum.start and prev_event_data is None:
continue
self.handle_object_detection(
camera, event_type, prev_event_data, event_data
)
elif input_type == EventTypeEnum.api:
self.handle_api_entry(camera, event_type, event_data)
def insert_or_save(
self,
entry: dict[str, Any],
prev_event_data: dict[Any, Any],
event_data: dict[Any, Any],
) -> None:
"""Insert into db or cache."""
id = entry[Timeline.source_id]
if not event_data["has_clip"] and not event_data["has_snapshot"]:
# the related event has not been saved yet, should be added to cache
if id in self.pre_event_cache.keys():
self.pre_event_cache[id].append(entry)
else:
self.pre_event_cache[id] = [entry]
else:
# the event is saved, insert to db and insert cached into db
if id in self.pre_event_cache.keys():
for e in self.pre_event_cache[id]:
Timeline.insert(e).execute()
self.pre_event_cache.pop(id)
Timeline.insert(entry).execute()
def handle_object_detection(
self,
camera: str,
event_type: str,
prev_event_data: dict[Any, Any],
event_data: dict[Any, Any],
) -> bool:
"""Handle object detection."""
save = False
camera_config = self.config.cameras[camera]
event_id = event_data["id"]
timeline_entry = {
Timeline.timestamp: event_data["frame_time"],
Timeline.camera: camera,
Timeline.source: "tracked_object",
Timeline.source_id: event_id,
Timeline.data: {
"box": to_relative_box(
camera_config.detect.width,
camera_config.detect.height,
event_data["box"],
),
"label": event_data["label"],
"sub_label": event_data.get("sub_label"),
"region": to_relative_box(
camera_config.detect.width,
camera_config.detect.height,
event_data["region"],
),
"attribute": "",
"score": event_data["score"],
},
}
# update sub labels for existing entries that haven't been added yet
if (
prev_event_data != None
and prev_event_data["sub_label"] != event_data["sub_label"]
and event_id in self.pre_event_cache.keys()
):
for e in self.pre_event_cache[event_id]:
e[Timeline.data]["sub_label"] = event_data["sub_label"]
if event_type == EventStateEnum.start:
timeline_entry[Timeline.class_type] = "visible"
save = True
elif event_type == EventStateEnum.update:
if (
len(prev_event_data["current_zones"]) < len(event_data["current_zones"])
and not event_data["stationary"]
):
timeline_entry[Timeline.class_type] = "entered_zone"
timeline_entry[Timeline.data]["zones"] = event_data["current_zones"]
save = True
elif prev_event_data["stationary"] != event_data["stationary"]:
timeline_entry[Timeline.class_type] = (
"stationary" if event_data["stationary"] else "active"
)
save = True
elif prev_event_data["attributes"] == {} and event_data["attributes"] != {}:
timeline_entry[Timeline.class_type] = "attribute"
timeline_entry[Timeline.data]["attribute"] = list(
event_data["attributes"].keys()
)[0]
if len(event_data["current_attributes"]) > 0:
timeline_entry[Timeline.data]["attribute_box"] = to_relative_box(
camera_config.detect.width,
camera_config.detect.height,
event_data["current_attributes"][0]["box"],
)
save = True
elif event_type == EventStateEnum.end:
timeline_entry[Timeline.class_type] = "gone"
save = True
if save:
self.insert_or_save(timeline_entry, prev_event_data, event_data)
def handle_api_entry(
self,
camera: str,
event_type: str,
event_data: dict[Any, Any],
) -> bool:
if event_type != "start":
return False
if event_data.get("type", "api") == "audio":
timeline_entry = {
Timeline.class_type: "heard",
Timeline.timestamp: event_data["start_time"],
Timeline.camera: camera,
Timeline.source: "audio",
Timeline.source_id: event_data["id"],
Timeline.data: {
"label": event_data["label"],
"sub_label": event_data.get("sub_label"),
},
}
else:
timeline_entry = {
Timeline.class_type: "external",
Timeline.timestamp: event_data["start_time"],
Timeline.camera: camera,
Timeline.source: "api",
Timeline.source_id: event_data["id"],
Timeline.data: {
"label": event_data["label"],
"sub_label": event_data.get("sub_label"),
},
}
Timeline.insert(timeline_entry).execute()
return True