* Add enum for type of classification for objects
* Update recognized license plate topic to be used as attribute updater
* Update attribute for attribute type object classification
* Cleanup
* semantic trigger test
* database and model
* config
* embeddings maintainer and trigger post-processor
* api to create, edit, delete triggers
* frontend and i18n keys
* use thumbnail and description for trigger types
* image picker tweaks
* initial sync
* thumbnail file management
* clean up logs and use saved thumbnail on frontend
* publish mqtt messages
* webpush changes to enable trigger notifications
* add enabled switch
* add triggers from explore
* renaming and deletion fixes
* fix typing
* UI updates and add last triggering event time and link
* log exception instead of return in endpoint
* highlight entry in UI when triggered
* save and delete thumbnails directly
* remove alert action for now and add descriptions
* tweaks
* clean up
* fix types
* docs
* docs tweaks
* docs
* reuse enum
* Ui improvements
* Improve image cropping and model saving
* Improve naming
* Add logs for training
* Improve model labeling
* Don't set sub label for none object classification
* Cleanup
* Ignore numpy get limits warning
* Add function wrapper to redirect stdout and stderr to logpipe
* Save stderr too
* Add more to catch
* run logpipe
* Use other logging redirect class
* Use other logging redirect class
* add decorator for redirecting c/c++ level output to logger
* fix typing
---------
Co-authored-by: Josh Hawkins <32435876+hawkeye217@users.noreply.github.com>
* 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>
* Combine base and arm trt detectors
* Remove unused deps for amd64 build
* Add missing packages and cleanup ldconfig
* Expand packages for tensorflow model training
* Cleanup
* Refactor training to not reserve memory
* Implement model training via ZMQ and add model states to represent training
* Get model updates working
* Improve toasts and model state
* Clean up logging
* Add back in
* Setup basic training structure
* Build out route
* Handle model configs
* Add image fetch APIs
* Implement model training screen with dataset selection
* Implement viewing of training images
* Adjust directories
* Implement viewing of images
* Add support for deleting images
* Implement full deletion
* Implement classification model training
* Improve naming
* More renaming
* Improve layout
* Reduce logging
* Cleanup
The PP_OCRv5 text detection models have greatly improved over v3. The v5 recognition model makes improvements to challenging handwriting and uncommon characters, which are not necessary for LPR, so using v4 seemed like a better choice to continue to keep inference time as low as possible. Also included is the full dictionary for Chinese character support.
* install new packages for transcription support
* add config options
* audio maintainer modifications to support transcription
* pass main config to audio process
* embeddings support
* api and transcription post processor
* embeddings maintainer support for post processor
* live audio transcription with sherpa and faster-whisper
* update dispatcher with live transcription topic
* frontend websocket
* frontend live transcription
* frontend changes for speech events
* i18n changes
* docs
* mqtt docs
* fix linter
* use float16 and small model on gpu for real-time
* fix return value and use requestor to embed description instead of passing embeddings
* run real-time transcription in its own thread
* tweaks
* publish live transcriptions on their own topic instead of tracked_object_update
* config validator and docs
* clarify docs
* Add basic config for defining a teachable machine model
* Add model type
* Add basic config for teachable machine models
* Adjust config for state and object
* Use config to process
* Correctly check for objects
* Remove debug
* Rename to not be teachable machine specific
* Cleanup
* Only check if an object is stationary to avoid mqtt snapshot
* docs heading tweak
* Add more API descriptions
* Add missing lib for new rocm onnxruntime whl
* Update inference times to reflect better rocm performance
* Cleanup resetting tracked object activity
* remove print
---------
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.
* Add camera name tooltip to previews in recording view
* Apply face area check to cv2 face detection
* Delete review thumbnails
* Don't import hailo until it is used
* Add comment
* Clean up camera name
* Filter out empty keys when updating yaml config
HA ingress seems to randomly add an equal sign to the PUT urls for updating the config from the UI. This fix prevents empty keys from being processed, but still allows empty values.
---------
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* Catch error and show toast when failing to delete review items
* i18n keys
* add link to speed estimation docs in zone edit pane
* Implement reset of tracked object update for each camera
* Cleanup
* register mqtt callbacks for toggling alerts and detections
* clarify snapshots docs
* clarify semantic search reindexing
* add ukrainian
* adjust date granularity for last recording time
The api endpoint only returns granularity down to the day
* Add amd hardware
* fix crash in face library on initial start after enabling
* Fix recordings view for mobile landscape
The events view incorrectly was displaying two columns on landscape view and it only took up 20% of the screen width. Additionally, in landscape view the timeline was too wide (especially on iPads of various screen sizes) and would overlap the main video
* face rec overfitting instructions
* Clarify
* face docs
* clarify
* clarify
---------
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* face library i18n fixes
* face library i18n fixes
* add ability to use ctrl/cmd S to save in the config editor
* Use datetime as ID
* Update metrics inference speed to start with 0 ms
* fix android formatted thumbnail
* ensure role is comma separated and stripped correctly
* improve face library deletion
- add a confirmation dialog
- add ability to select all / delete faces in collections
* Implement lazy loading for video previews
* Force GPU for large embedding model
* GPU is required
* settings i18n fixes
* Don't delete train tab
* webpush debugging logs
* Fix incorrectly copying zones
* copy path data
* Ensure that cache dir exists for Frigate+
* face docs update
* Add description to upload image step to clarify the image
* Clean up
---------
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* fix onvif reinitialization
* api docs: clarify usage of clip.mp4 endpoint
* Always show train tab
* Add description to API
* catch lpr model inference exceptions
* always apply motion mask when using yolov9 plate detection
* lpr faq
* fix incorrect focus when reopening search detail dialog on video tab
* only use keyboard listener in face library when train tab is active
---------
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* Send tracked object updates for face and license_plate objects
* Update docs
* Add to type enum
* Add camera to object description update
* Formatting
* Consolidate yue-Hant
* Add missing
* Only auto-populate some config fields down to the camera level
- Don't populate LPR and face global-only settings down to the camera level
- Ensure LPR mixin uses camera level min_area
- Explicitly forbid extra config values for LPR and face
* lpr docs tweak
* remove extra text already in i18n key
* consistency
* add support for multi-line plates
* config for model size
* default to small model
* add license plate as attribute to motorcycle
* use model size
* docs
* attribute map
* i18n key fix
* Merge nearby horizontal boxes
* only publish to recognized plate field if object already has a sub label
* don't overwrite sub labels in any situation
* always publish sub label if it's a known plate
* 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
* Section faces by event id
* Make score keeping more robust
* layout improvements
* Cleanup dialog
* Fix clicking behavior
* Add view in explore option
* math.round
* Don't require events
* Cleanup
* Remove selection
* Don't require
* Change dialog size with snapshot
* Use filename as key
* fix key
* Rework layout for mobile
* Handle mobile landscape
* Fix train issue
* Match logic
* Move deletion logic
* Fix reprocessing
* Support creating a new face
* Translations
* Do sorting in frontend
* Adjust unknown
* Cleanup
* Set max limit to faces to recognize
* Fix sorting
* Fix
* add config validator for face and lpr
* more lpr docs tweaks
* fix object lifecycle point clicking for aspect ratios less than 16/9
* fix semantic search indexing i18n keys
* remove ability to set system language
* clarify debug output
* Don't assume landmark file is downloaded
* Rewrite build model task to be asynchronous so it doesn't block the pipeline
* Handle case where face recognition does not respond
* Cleanup
* Make daemon thread
