* 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.
* add regex support to events api for recognized_license_plate
* frontend
add ability to use regexes in the plate search box and add select all/clear all links to quickly select all filtered plates
* use custom swr fetcher to check for audio support
The go2rtc API doesn't always return stream data for anything not being actively consumed, so audio support was not always being correctly deduced. So we can use a custom swr fetcher to call the endpoint that probes the streams, which returns the correct producers data.
* return correct mime type for thumbnail and latest frame endpoints
follow up to https://github.com/blakeblackshear/frigate/pull/19555
* 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
* 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
* 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
* 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
* 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>
* 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
* 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
* 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
* 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
* 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
* Include preferred startTime in source so that the playlist does not need to seek
* Compatibility
* Cleanup
* Adjust based on inpoint
* Don't set start position if it is not valid
* Handle firefox buggy behavior
* Fetch all license plates outside of filter component
If the swr call took a long time, the entire select component may not display. This change moves the fetch to the parent component (like sub labels).
* add loading indicator
* improve query
