* 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
* 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
* 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
* 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
* 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
* 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
* Remove old genai docs
* Separate existing genai docs to separate sections
* Add docs for genai features
* Update reference config
* Update link
* Move to bottom
* 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
* 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
* 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
