* update live view docs
* use swr as single source of truth for searchDetail
rather than maintaining a separate state, derive the selected item from swr cache. fixes websocket sync when regenerating descriptions or fetching transcriptions
* fix key warning in console
* don't try to fetch event from review item for audio events
* update audio transcription toast wording
* Add a community supported badge to specific detectors in the info summaries to better separate
* Make object classification publish to tracked object update and add examples for state classification
* Add item to advanced docs about tensorflow limiting
* Don't show submission for in progress objects
* fix for ios not reporting video dimensions on initial metadata load
in testing, polling with requestAnimationFrame finds the dimensions within 2 frames
* Catch jetson nvidia device tree
---------
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* Don't warn when event ids have expired for trigger sync
* Import faster_whisper conditinally to avoid illegal instruction
* Catch OpenVINO runtime error
* fix race condition in detail stream context
navigating between tracked objects in Explore would sometimes prevent the object track from appearing
* Handle case where classification images are deleted
* Adjust default rounded corners on larger screens
* Improve flow handling for classification state
* Remove images when wizard is cancelled
* Improve deletion handling for classes
* Set constraints on review buffers
* Update to support correct data format
* Set minimum duration for recording based review items
* Use friendly name in review genai prompt
---------
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* remove frigate+ icon from explore grid footer
* add margin
* pointer cursor on event menu items in detail stream
* don't show submit to plus for non-objects and if plus is disabled
* tweak spacing in annotation settings popover
* Fix deletion of classification images and library
* Ensure after creating a class that things are correct
* Fix dialog getting stuck
* Only show the genai summary popup on mobile when timeline is open
* fix audio transcription embedding
* spacing
* hide x icon on restart sheet to prevent closure issues
* prevent x overflow in detail stream on mobile safari
* ensure name is valid for search effect trigger
* add trigger to detail actions menu
* move find similar to actions menu
* Use a column layout for MobilePageContent in PlatformAwareSheet
This is so the header is outside the scrolling area and the content can grow/scroll independently. This now matches the way it's done in classification
* Skip azure execution provider
* add optional ref to always scroll to top
the more filters in explore was not scrolled to the top on open due to the use of framer motion
* fix title classes on desktop
---------
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* Correctly remove classification model from config
* Undo
* fix
* Use existing config update API and dynamically remove models that were running
* Set update message for face
* Implement extraction of images for classification state models
* Add object classification dataset preparation
* Add first step wizard
* Update i18n
* Add state classification image selection step
* Improve box handling
* Add object selector
* Improve object cropping implementation
* Fix state classification selection
* Finalize training and image selection step
* Cleanup
* Design optimizations
* Cleanup mobile styling
* Update no models screen
* Cleanups and fixes
* Fix bugs
* Improve model training and creation process
* Cleanup
* Dynamically add metrics for new model
* Add loading when hitting continue
* Improve image selection mechanism
* Remove unused translation keys
* Adjust wording
* Add retry button for image generation
* Make no models view more specific
* Adjust plus icon
* Adjust form label
* Start with correct type selected
* Cleanup sizing and more font colors
* Small tweaks
* Add tips and more info
* Cleanup dialog sizing
* Add cursor rule for frontend
* Cleanup
* remove underline
* Lazy loading
* camera level config
* set up model runner on thread start to avoid unpickling error
* ensure feature is enabled globally
* suppress info logs from faster_whisper
* fix incorrect event_type for api and audio timeline entries
* docs
* fix
* clean up
* refactor get_video_properties and use json output from ffprobe
* add zmq topic
* publish valid segment data in recording maintainer
* check for valid video data
- restart separate record ffmpeg process if no video data has been received in 120s
- refactor datetime import
* listen to correct topic in embeddings maintainer
* refactor to move get_latest_segment_datetime logic to recordings maintainer
* debug logging
* cleanup
* continue to use paddleocr v3 text detection model for large
v5 was not finding text on multi-line plates at all in testing
* implement clustering of plate variants per event
should reduce OCR inconsistencies and improve plate recognition stability by using string similarity to cluster similar variants (10 per event id) and choosing the highest confidence representative as the final plate
* pass camera
* prune number of variants based on detect fps
* implement replacement rules for cleaning up and normalizing plates
* docs
* docs
* Cleanup onnx detector
* Fix
* Fix classification cropping
* Deprioritize openvino
* Send model type
* Use model type to decide if model can use full optimization
* Clenanup
* Cleanup
* Use re-usable inference request to reduce CPU usage
* Share tensor
* Don't count performance
* Create openvino runner class
* Break apart onnx runner
* Add specific note about inability to use CUDA graphs for some models
* Adjust rknn to use RKNNRunner
* Use optimized runner
* Add support for non-complex models for CudaExecutionProvider
* Use core mask for rknn
* Correctly handle cuda input
* Cleanup
* Sort imports
* Generate review item summaries with requests
* Adjust logic to only send important items
* Don't mention ladder
* Adjust prompt to be more specific
* Add more relaxed nature for normal activity
* Cleanup summary
* Update ollama client
* Add more directions to analyze the frames in order
* Remove environment from prompt
* Include extra level for normal activity
* Add dynamic toggling
* Update docs
* Add different threshold for genai
* Adjust webUI for object and review description feature
* Adjust config
* Send on startup
* Cleanup config setting
* Set config
* Fix config name
* 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
* 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>
* Move log level initialization to log
* Use logger config
* Formatting
* Fix config order
* Set process names
---------
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.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>
* 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>
* 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
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
* fix embeddings reindex
- always increment processed objects to prevent division by zero
- ensure description still gets processed even if there is no thumbnail
* clean up
* Add newer labels to default attribute map
---------
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
