* Set runtime
* Use count correctly
* Don't assume camera sizes
* Use separate zmq proxy for object detection
* Correct order
* Use forkserver
* Only store PID instead of entire process reference
* Cleanup
* Catch correct errors
* Fix typing
* Remove before_run from process util
The before_run never actually ran because:
You're right to suspect an issue with before_run not being called and a potential deadlock. The way you've implemented the run_wrapper using __getattribute__ for the run method of BaseProcess is a common pitfall in Python's multiprocessing, especially when combined with how multiprocessing.Process works internally.
Here's a breakdown of why before_run isn't being called and why you might be experiencing a deadlock:
The Problem: __getattribute__ and Process Serialization
When you create a multiprocessing.Process object and call start(), the multiprocessing module needs to serialize the process object (or at least enough of it to re-create the process in the new interpreter). It then pickles this serialized object and sends it to the newly spawned process.
The issue with your __getattribute__ implementation for run is that:
run is retrieved during serialization: When multiprocessing tries to pickle your Process object to send to the new process, it will likely access the run attribute. This triggers your __getattribute__ wrapper, which then tries to bind run_wrapper to self.
run_wrapper is bound to the parent process's self: The run_wrapper closure, when created in the parent process, captures the self (the Process instance) from the parent's memory space.
Deserialization creates a new object: In the child process, a new Process object is created by deserializing the pickled data. However, the run_wrapper method that was pickled still holds a reference to the self from the parent process. This is a subtle but critical distinction.
The child's run is not your wrapped run: When the child process starts, it internally calls its own run method. Because of the serialization and deserialization process, the run method that's ultimately executed in the child process is the original multiprocessing.Process.run or the Process.run if you had directly overridden it. Your __getattribute__ magic, which wraps run, isn't correctly applied to the Process object within the child's context.
* Cleanup
* Logging bugfix (#18465)
* use mp Manager to handle logging queues
A Python bug (https://github.com/python/cpython/issues/91555) was preventing logs from the embeddings maintainer process from printing. The bug is fixed in Python 3.14, but a viable workaround is to use the multiprocessing Manager, which better manages mp queues and causes the logging to work correctly.
* consolidate
* fix typing
* Fix typing
* Use global log queue
* Move to using process for logging
* Convert camera tracking to process
* Add more processes
* Finalize process
* Cleanup
* Cleanup typing
* Formatting
* Remove daemon
---------
Co-authored-by: Josh Hawkins <32435876+hawkeye217@users.noreply.github.com>
* Add base class for global config updates
* Add or remove camera states
* Move camera process management to separate thread
* Move camera management fully to separate class
* Cleanup
* Stop camera processes when stop command is sent
* Start processes dynamically when needed
* Adjust
* Leave extra room in tracked object queue for two cameras
* Dynamically set extra config pieces
* Add some TODOs
* Fix type check
* Simplify config updates
* Improve typing
* Correctly handle indexed entries
* Cleanup
* Create out SHM
* Use ZMQ for signaling object detectoin is completed
* Get camera correctly created
* Cleanup for updating the cameras config
* Cleanup
* Don't enable audio if no cameras have audio transcription
* Use exact string so similar camera names don't interfere
* Add ability to update config via json body to config/set endpoint
Additionally, update the config in a single rather than multiple calls for each updated key
* fix autotracking calibration to support new config updater function
---------
Co-authored-by: Josh Hawkins <32435876+hawkeye217@users.noreply.github.com>
* Add option to not trim clip
* Improve API
* Update snapshot for new best objects
* Fix missing strings
* Convert to separate key
* Always include bounding box on snapshots
* improve autotracking relative zooming time calculation
* update proxy docs to note the need for comma separated header roles
* Add count translation
* tracked object lifecycle i18n fix
* update speed estimation docs
* clarity
* Re-initialize onvif information when toggling camera on live view
* Move time ago to card info and add face area
* Clarify face recognition docs
* Increase minimum face recognition area
* use clipFrom to in vod module endpoint to start at the correct time
* Cleanup media api
* Don't change duration
* Use search detail dialog for face library
* Move to segment based
* Cleanup
* Add back duration modification
* clean up docs
---------
Co-authored-by: Josh Hawkins <32435876+hawkeye217@users.noreply.github.com>
* Fix the `Any` typing hint treewide
There has been confusion between the Any type[1] and the any function[2]
in typing hints.
[1] https://docs.python.org/3/library/typing.html#typing.Any
[2] https://docs.python.org/3/library/functions.html#any
* Fix typing for various frame_shape members
Frame shapes are most likely defined by height and width, so a single int
cannot express that.
* Wrap gpu stats functions in Optional[]
These can return `None`, so they need to be `Type | None`, which is what
`Optional` expresses very nicely.
* Fix return type in get_latest_segment_datetime
Returns a datetime object, not an integer.
* Make the return type of FrameManager.write optional
This is necessary since the SharedMemoryFrameManager.write function can
return None.
* Fix total_seconds() return type in get_tz_modifiers
The function returns a float, not an int.
https://docs.python.org/3/library/datetime.html#datetime.timedelta.total_seconds
* Account for floating point results in to_relative_box
Because the function uses division the return types may either be int or
float.
* Resolve ruff deprecation warning
The config has been split into formatter and linter, and the global
options are deprecated.
* Save initial frame of new objects to frame cache
Objects that move quickly through the frame and are only seen briefly may not have the update() method called to save thumbnail_data, and may not have the initial frame saved to the tracked object frame cache. This caused a "Frame missing from frame cache" message that was patched by #7313 but this sometimes caused the wrong frame to be chosen for the thumb/snapshot.
* Tracking tweaks
- When registering new objects, use the past detections from Norfair to populate self.positions and self.stationary_box_history. This prevents the first call of update_position() from triggering a +1 on the object's stationary count (because the iou would be 1.0).
- Add a specific tracker for dedicated LPR cam license_plate objects using a lower R value and higher distance threshold to account for fast moving plates.
- Add helpful debug messages and keep them disabled with `if False:`
* Correctly ensure updates are more periodic when lpr or face detection is needed
* Cleanup
* Update api schema
* Don't update for stationary objects
* Simplify check
* Remove
* remove license plate from attributes for dedicated lpr cameras
* ensure we always have a color
* use frigate+ models with dedicated lpr cameras
* docs
* docs clarity
* docs enrichments
* use license_plate as object type
* Increase frequency of updates when internal face detection is used
* Adjust number of required faces based on detection type
* Adjust min_score config to unknown_score
* Only for person
* Improve typing
* Update face rec docs
* Cleanup ui colors
* Cleanup
* config options
* processing in maintainer
* detect and process dedicated lpr plates
* create camera type, add manual event and save snapshot
* use const
* ensure lpr events are always detections, typing fixes
* docs
* docs tweaks
* add preprocessing and penalization for low confidence chars
* Fix case where objects are returned as null
* Fix enabled status not being persisted
* Use config as source of truth when refreshed
* Ensure camera always have config object updated
* Cleanup typing
* backend
* backend fixes
* api for search queries
* frontend
* docs
* add filterable scroll list to more filters pane for identifiers
* always publish identifier
* config options
* metrics
* stop and restart ffmpeg processes
* dispatcher
* frontend websocket
* buttons for testing
* don't recreate log pipe
* add/remove cam from birdseye when enabling/disabling
* end all objects and send empty camera activity
* enable/disable switch in ui
* disable buttons when camera is disabled
* use enabled_in_config for some frontend checks
* tweaks
* handle settings pane with disabled cameras
* frontend tweaks
* change to debug log
* mqtt docs
* tweak
* ensure all ffmpeg processes are initially started
* clean up
* use zmq
* remove camera metrics
* remove camera metrics
* tweaks
* frontend tweaks
* Subclass Process for audio_process
* Introduce custom mp.Process subclass
In preparation to switch the multiprocessing startup method away from
"fork", we cannot rely on os.fork cloning the log state at fork time.
Instead, we have to set up logging before we run the business logic of
each process.
* Make camera_metrics into a class
* Make ptz_metrics into a class
* Fixed PtzMotionEstimator.ptz_metrics type annotation
* Removed pointless variables
* Do not start audio processor when no audio cameras are configured
