* tweak api to fetch multiple timelines
* support multiple selected objects in context
* rework context provider
* use toggle in detail stream
* use toggle in menu
* plot multiple object tracks
* verified icon, recognized plate, and clicking tweaks
* add plate to object lifecycle
* close menu before opening frigate+ dialog
* clean up
* normal text case for tooltip
* capitalization
* use flexbox for recording view
* 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
* Add cutoff for object classification
* Add selector for classifiction model type
* Improve model selection view
* Clean up design of classification card
* Tweaks
* Adjust button colors
* Improvements to gradients and making face library consistent
* Add basic classification model wizard
* Use relative coordinates
* Properly get resolution
* Clean up exports
* Cleanup
* Cleanup
* Update to use pre-defined component for image shadow
* Refactor image grouping
* Clean up mobile
* Clean up decision logic
* Remove max check on classification objects
* Increase default number of faces shown
* Cleanup
* Improve mobile layout
* Clenaup
* Update vocabulary
* Fix layout
* Fix page
* Cleanup
* Choose last item for unknown objects
* Move explore button
* Cleanup grid
* Cleanup classification
* Cleanup grid
* Cleanup
* Set transparency
* Set unknown
* Don't filter all configs
* Check length
* Add optional idle heartbeat for Birdseye (periodic frame emission when idle)
birdseye: add optional idle heartbeat and FFmpeg tuning envs (default off)
This adds an optional configuration field `birdseye.idle_heartbeat_fps` to
enable a lightweight idle heartbeat mechanism in Birdseye. When set to a value
greater than 0, Birdseye periodically re-sends the last composed frame during
idle periods (no motion or active updates).
This helps downstream consumers such as go2rtc, Alexa, or Scrypted to attach
faster and maintain a low-latency RTSP stream when the system is idle.
Key details:
- Config-based (`birdseye.idle_heartbeat_fps`), default `0` (disabled).
- Uses existing Birdseye rendering pipeline; minimal performance impact.
- Does not alter behavior when unset.
Documentation: added tip section in docs/configuration/restream.md.
* Update docs/docs/configuration/restream.md
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* Update docs/docs/configuration/reference.md
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* Refactors Birdseye idle frame broadcasting
Simplifies the idle frame broadcasting logic by removing the dedicated thread.
The idle frame is now resent directly within the main loop,
improving efficiency and reducing complexity. Also, limits the idle
heartbeat FPS to a maximum of 10 since the framebuffer is limited to 10 anyway
* ruff fix
---------
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
Co-authored-by: Francesco Durighetto <francesco.durighetto@subbyx.com>
Co-authored-by: duri <duri@homelabubuntu.durihome.unifi>
* save clean webp instead of png
* send clean webp to plus with fallback for old events
* manual event webp
* event cleanup
* api def
* convert png to webp if exists
* update reference config
* change quality
* Migrate camera APIs to separate tag
* Implement reolink detection to handle dynamic URL assignment
* Cleanup codec handling
* Use average framerate not relative framerate
* Add reolink rtsp warning
* Don't return exception
* Use avg_frame_rate in final info
* Clenaup
* Validate host
* Fix overlap
* fetch more from ffprobe
* add detailed param to ffprobe endpoint
* add dots variant to step indicator
* add classname
* tweak colors for dark mode to match figma
* add step 1 form
* add helper function for ffmpeg snapshot
* add go2rtc stream add and ffprobe snapshot endpoints
* add camera image and stream details on successful test
* step 1 tweaks
* step 2 and i18n
* types
* step 1 and 2 tweaks
* add wizard to camera settings view
* add data unit i18n keys
* restream tweak
* fix type
* implement rough idea for step 3
* add api endpoint to delete stream from go2rtc
* add main wizard dialog component
* extract logic for friendly_name and use in wizard
* add i18n and popover for brand url
* add camera name to top
* consolidate validation logic
* prevent dialog from closing when clicking outside
* center camera name on mobile
* add help/docs link popovers
* keep spaces in friendly name
* add stream details to overlay like stats in liveplayer
* add validation results pane to step 3
* ensure test is invalidated if stream is changed
* only display validation results and enable save button if all streams have been tested
* tweaks
* normalize camera name to lower case and improve hash generation
* move wizard to subfolder
* tweaks
* match look of camera edit form to wizard
* move wizard and edit form to its own component
* move enabled/disabled switch to management section
* clean up
* fixes
* fix mobile
* new body param
* use new body param in endpoint
* explicitly use new param in frontend endpoint
* use reviewsegment as type instead of list of strings
* add toggle function to mark as unreviewed when all selected are reviewed
* i18n
* fix tests
* Map verified objects to their sub label directly
* Simplify access
* Cleanup
* Add protection for mismatched object and index
* Keep track of verified objects separately
* 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
* Update classification API docs
* Add information to events api
* Fix tag
* Add exports
* Add generic response to model for classification apis
* Add preview API information
* Cleanup
* Cleanup
* Refactor face card into generic classification card
* Update classification data card to use classification card
* Refactor state training grid to use classification card
* Refactor grouped face card into generic component
* Combine classification objects by event
* Fixup
* Cleanup
* Cleanup
* Do not fail if a single event is not found
* Save original frame
* Cleanup
* Undo
* Improve prompt to have better discernment and logic based on detected objects
* Be more specific about the time of day
* Add re-inforcers for LLM to be accurate and not complete a narrative
* 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
* Update ROCm to 7.0.1
* Update ONNXRuntime
* Add back in
* Get basic detection working
* Use env vars
* Handle complex migraphx models
* Enable model caching
* Remove unused
* Add tip to docs
* [Init] Initial commit for Synaptics SL1680 NPU
* add a rough detector which is testing with yolov8 tflite model.
* [Feat] Add dependencies installation in docker build
- Add runtime library and wheels installation in main/Dockerfile
- Add model.synap(default model, transfer from mobilenet_224full80) in docker/synap1680
* [Update] Remove dependencies installation from main Dockerfile
- remove deps installation from Dockerfile
- add dependencies installation and split wheels, deps stage in synap1680 Dockerfile
* Refactor synap detector to more closely match other implementations
* [Update] Add model path configuration check
* [Update] update ModelType to ssd
* [Update] Remove unuse script
- install_deps.sh has already been executing in deps download stage
- Dockerfile.toolchain is for testing to extract runtime libraries from Synaptics toolchain
* [Update] update Synaptics SL1680 setup description
* [Update] remove install_synap1680
- The deps download and installation is existed in synap1680
* [Fix] update document content
* [Update] Update detector from synap1680 to synaptics
This update is in order to make the synaptics SL-series NPU detector more general.
- Fix detector `os` module not import bug
- Update detector type `synap1680` to `synaptics`
- Update document description `SL1680` to `Synaptics` only
- Update docker build content `synap1680` to `synaptics`
* [Fix] Update configuration document
* Update docs/docs/configuration/object_detectors.md
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* [Update] Update document content and detector default layout
- Update object_detectors document
- Update detector's default layout
- Update default model name
* [Update] Update object detector document content
* [Fix] Fix InputTensorEnum not defined error
- import InputTensorEnum from detector_config
* [Update] Update detector script coding format
* [Update] Update synaptics detector coding format
* [Update] Add synaptics ci workflow
* [Update] update synaptics runtime libs download path
- Fork Synaptics astra sdk repo and put the runtime lib package on it
- Frigate team can update this download path later
---------
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* Implement stationary car classifier to base stationary state on visual changes and not just bounding box stability
* Cleanup
* Fix mypy
* Move to new file and add config to disable if needed
* Cleanup
* Undo
This supports systemd credentials, see https://systemd.io/CREDENTIALS/.
Default to `/run/secrets` (the Docker Secrets dir) for backwards
compatibility.
* pull count of detection events by label into prometheus metrics
* format changes with ruff
* remove unneeded f-string
* fix imports format
---------
Co-authored-by: iesad <iesad>
* 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 OpenVINO directly to detect if devices are available
* Cleanup
* Update OpenVINO
* Cleanup
* Don't try to use OpenVINO when CPU is set as device
* Catch case where input tensor can't be pre-defined
* 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
* update config for roles and add validator
* ensure admin and viewer are never overridden
* add class method to user to retrieve all allowed cameras
* enforce config roles in auth api endpoints
* add camera access api dependency functions
* protect review endpoints
* protect preview endpoints
* rename param name for better fastapi injection matching
* remove unneeded
* protect export endpoints
* protect event endpoints
* protect media endpoints
* update auth hook for allowed cameras
* update default app view
* ensure anonymous user always returns all cameras
* limit cameras in explore
* cameras is already a list
* limit cameras in review/history
* limit cameras in live view
* limit cameras in camera groups
* only show face library and classification in sidebar for admin
* remove check in delete reviews
since admin role is required, no need to check camera access. fixes failing test
* pass request with camera access for tests
* more async
* camera access tests
* fix proxy auth tests
* allowed cameras for review tests
* combine event tests and refactor for camera access
* fix post validation for roles
* don't limit roles in create user dialog
* fix triggers endpoints
no need to run require camera access dep since the required role is admin
* fix type
* create and edit role dialogs
* delete role dialog
* fix role change dialog
* update settings view for roles
* i18n changes
* minor spacing tweaks
* docs
* use badges and camera name label component
* clarify docs
* display all cameras badge for admin and viewer
* i18n fix
* use validator to prevent reserved and empty roles from being assigned
* split users and roles into separate tabs in settings
* tweak docs
* clarify docs
* change icon
* don't memoize roles
always recalculate on component render
* Use asyncio lock when checking camera status
get_camera_status() can be called during normal autotracking movement and from routine camera_maintenance(). Some cameras cause one of the status calls to hang, which then subsequently hangs autotracking. A lock serializes access and prevents the hang.
* use while loop in camera_maintenance for status check
some cameras seem to take a little bit to update their status, don't assume the first call shows the motor has stopped
* Refactor active objects to class
* Keep segment going when detection is newer than end of alert
* Cleanup logic
* Fix
* Cleanup ending
* Adjust timing
* Improve detection saving
* Don't have padding at end for in progress reviews
* Add review config for cutoff times
* Added degirum plugin, updated documentation for degirum detector usage, updated requirements with degirum_headless
* Fixed broken link
* Made it so openvino prioritizes using GPU and NPU over CPU
* Version that detects model and can begin using @local
* Updating requirements to build dev container
* Added optimized version of degirum plugin + updated docs
* Added guard clause for empty inference reponse
* Updated DeGirum's docs
* Moved DeGirum section to 'Community' detectors, fixed formatting of headers to be more consistent with the rest of the page, and removed uneeded 'models' folder
* Moved DeGirum section to correct place in community models
* Update ROCm to 6.4.0 (#18264)
* Update to rocm 6.4.0
* Update URL
* Remove old env var
* Dynamic Config Updates (#18353)
* Create classes to handle publishing and subscribing config updates
* Cleanup
* Use config updater
* Update handling for enabled config
* Cleanup
* Recording config updates
* Birdseye config updates
* Handle notifications
* handle review
* Update motion
* Dynamically update masks and zones for cameras (#18359)
* Include config publisher in api
* Call update topic for passed topics
* Update zones dynamically
* Update zones internally
* Support zone and mask reset
* Handle updating objects config
* Don't put status for needing to restart Frigate
* Cleanup http tests
* Fix tests
* Initial custom classification model config support (#18362)
* 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
* Implement support for no recordings indicator on timeline (#18363)
* Indicate no recordings on the history timeline with gray hash marks
This commit includes a new backend API endpoint and the frontend changes needed to support this functionality
* don't show slashes for now
* Update ROCm to 6.4.1 (#18364)
* Update rocm to 6.4.1
* Quick fix
* Add ability to configure when custom classification models run (#18380)
* Add config to control when classification models are run
* Cleanup
* Add basic config editor when Frigate can't startup (#18383)
* Start Frigate in safe mode when config does not validate
* Add safe mode page that is just the config editor
* Adjust Frigate config editor when in safe mode
* Cleanup
* Improve log message
* Fix incorrectly running lpr (#18390)
* Audio transcription support (#18398)
* 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
* Implement API to train classification models (#18475)
* Intel updates (#18493)
* Update openvino and onnxruntime
* Install icd and level-zero-gpu deps from intel directly
* Install
* Add dep
* Fix package install
* Tiered recordings (#18492)
* Implement tiered recording
* Add migration for record config
* Update docs
* Update reference docs
* Fix preview query
* Fix incorrect accesses
* Fix
* Fix
* Fix
* Fix
* Upgrade PaddleOCR models to v4 (rec) and v5 (det) (#18505)
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.
* Audio transcription tweaks (#18540)
* use model runner
* unload whisper model when live transcription is complete
* Classification Model UI (#18571)
* 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
* Live classification model training (#18583)
* 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
* Classification Model Metrics (#18595)
* Add speed and rate metrics for custom classification models
* Use metrics for classification models
* Use keys
* Cast to list
* Add Mesa Teflon as a TFLite detector (#18310)
* Refactor common functions for tflite detector implementations
* Add detector using mesa teflon delegate
Non-EdgeTPU TFLite can use the standard .tflite format
* Add mesa-teflon-delegate from bookworm-backports to arm64 images
* feat: enable using GenAI for cameras with GenAI disabled from the API (#18616)
* fix: Initialize GenAI client if GenAI is enabled globally (#18623)
* Make Birdseye clickable (#18628)
* keep track of layout changes and publish on change
* websocket hook
* clickable overlay div to navigate to full camera view
* Refactor TensorRT (#18643)
* 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
* Dynamic Management of Cameras (#18671)
* 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>
* Use Fork-Server As Spawn Method (#18682)
* 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 basic camera settings to UI for testing (#18690)
* add basic camera add/edit pane to the UI for testing
* only init model runner if transcription is enabled globally
* fix role checkboxes
* Ensure logging config is propagated to forked processes (#18704)
* Move log level initialization to log
* Use logger config
* Formatting
* Fix config order
* Set process names
---------
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* Fix go2rtc init (#18708)
* Cleanup process handling
* Adjust process name
* Reduce tf initialization
* Don't use staticmethod
* Don't fail on unicode debug for config updates
* Catch unpickling error
* Fix birdseye crash when dynamically adding a camera (#18821)
* Catch invalid character index in lpr CTC decoder (#18825)
* Classification model cover images (#18843)
* Move to separate component
* Add cover images for clssification models
* Fix process name
* Handle SIGINT with forkserver (#18860)
* Pass stopevent from main start
* Share stop event across processes
* preload modules
* remove explicit os._exit call
---------
Co-authored-by: Josh Hawkins <32435876+hawkeye217@users.noreply.github.com>
* Don't try to close or join mp manager queues (#18866)
Multiprocessing Manager queues don't have a close() or join_thread() method, and the Manager will clean it up appropriately after we empty it. This prevents an infinite loop when an AttributeError exception fires for Manager AutoProxy queue objects.
* Improve logging (#18867)
* 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>
* Add ONVIF focus support (#18883)
* backend
* frontend and i18n
* 0.17 tweaks (#18892)
* Set version
* Cleanup more logs
* Don't log matplotlib
* Improve object classification (#18908)
* 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
* Remove TFLite init logs
* Improve classification UI (#18910)
* Move threhsold to base model config
* Improve score handling
* Add back button
* Classification improvements (#19020)
* Move classification training to full process
* Sort class images
* Semantic Search Triggers (#18969)
* 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
* Optionally show tracked object paths in debug view (#19025)
* Dynamically enable/disable GenAI (#19139)
* config
* dispatcher and mqtt
* docs
* use config updater
* add switch to frontend
* Classification train updates (#19173)
* Improve model train button
* Add filters for classification
* Cleanup
* Don't run classification on false positives
* Cleanup filter
* Fix icon color
* Object attribute classification (#19205)
* 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
* Require setting process priority for FrigateProcess (#19207)
* Add bookworm-backports to the rocm images and upgrade mesa/vaapi to support RDNA4 GPUs (#19312)
* Improve the tablet layout (#19320)
* Improve the tablet layout
* Update imports sort
* Fix more imports
* Implement start for review item description processor (#19352)
* Add review item data transmission
* Publish review updates
* Add review item subscriber
* Basic implementation for testing review processor
* Formatting
* Cleanup
* Improve comms typing (#18599)
* Enable mypy for comms
* Make zmq data types consistent
* Cleanup inter process typing issues
* Cleanup embeddings typing
* Cleanup config updater
* Cleanup recordings updator
* Make publisher have a generic type
* Cleanup event metadata updater
* Cleanup event metadata updater
* Cleanup detections updater
* Cleanup websocket
* Cleanup mqtt
* Cleanup webpush
* Cleanup dispatcher
* Formatting
* Remove unused
* Add return type
* Fix tests
* Fix semantic triggers config typing
* Cleanup
* Ensure alertVideos persistence is loaded before displaying thumb or preview (#19432)
The default value of true would cause previews to be loaded in the background even if the local storage value was false
* Adjust loitering behavior based on object type (#19433)
* Adjust loitering behavior based on object
* Update docs
* Grammar
* Enable mypy for DB and fix types (#19434)
* Install peewee type hints
* Models now have proper types
* Fix iterator type
* Enable debug builds with dev reqs installed
* Install as wheel
* Fix cast type
* Migrate object genai configuration (#19437)
* Move genAI object to objects section
* Adjust config propogation behavior
* Refactor genai config usage
* Automatic migration
* Always start the embeddings process
* Always init embeddings
* Config fixes
* Adjust reference config
* Adjust docs
* Formatting
* Fix
* Review Item GenAI metadata (#19442)
* Rename existing function
* Keep track of thumbnial updates
* Tinkering with genai prompt
* Adjust input format
* Create model for review description output
* testing prompt changes
* Prompt improvements and image saving
* Add config for review items genai
* Use genai review config
* Actual config usage
* Adjust debug image saving
* Fix
* Fix review creation
* Adjust prompt
* Prompt adjustment
* Run genai in thread
* Fix detections block
* Adjust prompt
* Prompt changes
* Save genai response to metadata model
* Handle metadata
* Send review update to dispatcher
* Save review metadata to DB
* Send review notification updates
* Quick fix
* Fix name
* Fix update type
* Correctly dump model
* Add card
* Add card
* Remove message
* Cleanup typing and UI
* Adjust prompt
* Formatting
* Add log
* Formatting
* Add inference speed and keep alive
* Review genai updates (#19448)
* 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
* Use preview frames for Review Descriptions (#19450)
* Use preview frames for genai
* Cleanup
* Adjust
* Add config for users to define additional concerns that GenAI should make note of in review summary (#19463)
* Don't default to openai
* Improve UI
* Allow configuring additional concerns that users may want the AI to note
* Formatting
* Add preferred language config
* Remove unused
* Added total camera fps, total processed fps, and total skipped fps to stats api (#19469)
Co-authored-by: Mark Francis <markfrancisonly@gmail.com>
* Genai review summaries (#19473)
* 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
* Add ability to pass additional args to Ollama (#19484)
* Call out recognized objects more specifically
* Cleanup
* Make keep_alive and options configurable
* Generalize
* Use for other providers
* Update GenAI docs for new review summaries feature (#19493)
* Remove old genai docs
* Separate existing genai docs to separate sections
* Add docs for genai features
* Update reference config
* Update link
* Move to bottom
* Improve natural language of prompt (#19515)
* Make sequence details human-readable so they are used in natural language response
* Cleanup
* Improve prompt and image selection
* Adjust
* Adjust sligtly
* Format time
* Adjust frame selection logic
* Debug save response
* Ignore extra fields
* Adjust docs
* Cleanup filename sanitization
* Added degirum plugin, updated documentation for degirum detector usage, updated requirements with degirum_headless
* Fixed broken link
* Made it so openvino prioritizes using GPU and NPU over CPU
* Version that detects model and can begin using @local
* Added optimized version of degirum plugin + updated docs
* Updating requirements to build dev container
* Added guard clause for empty inference reponse
* Updated DeGirum's docs
* Moved DeGirum section to 'Community' detectors, fixed formatting of headers to be more consistent with the rest of the page, and removed uneeded 'models' folder
* Moved DeGirum section to correct place in community models
* Added degirum plugin, updated documentation for degirum detector usage, updated requirements with degirum_headless
* Fixed broken link
* Made it so openvino prioritizes using GPU and NPU over CPU
* Version that detects model and can begin using @local
* Added optimized version of degirum plugin + updated docs
* Updating requirements to build dev container
* Added guard clause for empty inference reponse
* Updated DeGirum's docs
* Moved DeGirum section to 'Community' detectors, fixed formatting of headers to be more consistent with the rest of the page, and removed uneeded 'models' folder
* Moved DeGirum section to correct place in community models
* Added degirum plugin, updated documentation for degirum detector usage, updated requirements with degirum_headless
* Fixed broken link
* Made it so openvino prioritizes using GPU and NPU over CPU
* Version that detects model and can begin using @local
* Added optimized version of degirum plugin + updated docs
* Updating requirements to build dev container
* Added guard clause for empty inference reponse
* Updated DeGirum's docs
* Moved DeGirum section to 'Community' detectors, fixed formatting of headers to be more consistent with the rest of the page, and removed uneeded 'models' folder
* Moved DeGirum section to correct place in community models
* Reverted changes to classification and audio
---------
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
Co-authored-by: Josh Hawkins <32435876+hawkeye217@users.noreply.github.com>
Co-authored-by: Jimmy <honj@alum.rpi.edu>
Co-authored-by: FL42 <46161216+fl42@users.noreply.github.com>
Co-authored-by: Steve Smith <tarkasteve@gmail.com>
Co-authored-by: markfrancisonly <12145270+markfrancisonly@users.noreply.github.com>
Co-authored-by: Mark Francis <markfrancisonly@gmail.com>
* refactor: Refactor camera nickname
* fix: fix cameraNameLabel visually
* chore: The Explore search function also displays the Camera's nickname in English
* chore: add mobile page camera nickname
* feat: webpush support camera nickname
* fix: fix storage camera name is null
* chore: fix review detail and context menu camera nickname
* chore: fix use-stats and notification setting camera nickname
* fix: fix stats camera if not nickname need capitalize
* fix: fix debug page open camera web ui i18n and camera nickname support
* fix: fix camera metrics not use nickname
* refactor: refactor use-camera-nickname hook.
