* add sub stream recording with adaptive quality playback
Optionally record a second, lower bitrate stream alongside the main
recording stream via a `record_sub` input role and `record.sub` config block, with its own retention windows.
Recordings rows now carry the stream type plus the media details needed to serve both streams from one manifest: video codec, audio presence, audio codec and rate, and a record-time keyframe index.
Playback resolves coverage across both streams and merges them into a single VOD sequence, falling back to a discontinuity manifest with per-clip init segments when the media signatures differ. The player exposes a quality selector, and an auto governor picks the stream from stall time, bandwidth, codec support, and the save-data hint.
* fix tests and i18n
* Pin ruff
* Add python upgrade fixes
This enables python upgrade checks in ruff to look for deprecated types and patterns. This namely fixes:
- usage of deprecated `Typing` which is now built in
- some specific exceptions which are caught and have new aliases
Some specific UP checks were also ignored as they are stylistic / unimportant and likely to cause bugs
* Remove async blocking calls
Use asyncio.to_thread on two remaining blocking calls to fix hanging event thread loop. Enable this specific rule to block it in the future.
* Use proper logging mechanism
* Correctly format logs
* Raise with context
When raising an exception include the from context to improve debugging
* Cleanup
* add randomness to object classification
also ensure train_dir is fresh if user has regenerated examples
* frontend refresh button
* fix radix dropdown issue
* i18n
* Strip model name before training
* Handle options file for go2rtc option
* Make reviewed optional and add null to API call
* Send reviewed for dashboard
* Allow setting context size for openai compatible endpoints
* push empty go2rtc config to avoid homekit error in log
* Add option to set runtime options for LLM providers
* Docs
---------
Co-authored-by: Josh Hawkins <32435876+hawkeye217@users.noreply.github.com>
* Fix genai callbacks in MQTT
* Cleanup cursor pointer for classification cards
* Cleanup
* Handle unknown SOCs for RKNN converter by only using known SOCs
* don't allow "none" as a classification class name
* change internal port user to admin and default unspecified username to viewer
* keep 5000 as anonymous user
* suppress tensorflow logging during classification training
* Always apply base log level suppressions for noisy third-party libraries even if no specific logConfig is provided
* remove decorator and specifically suppress TFLite delegate creation messages
---------
Co-authored-by: Josh Hawkins <32435876+hawkeye217@users.noreply.github.com>
* Wait for config to load before evaluating route access
Fix race condition where custom role users are temporarily denied access after login while config is still loading. Defer route rendering in DefaultAppView until config is available so the complete role list is known before ProtectedRoute evaluates permissions
* Use batching for state classification generation
* Ignore incorrect scoring images if they make it through the deletion
* Delete unclassified images
* mitigate tensorflow atexit crash by pre-importing tflite/tensorflow on main thread
Pre-import Interpreter in embeddings maintainer and add defensive lazy imports in classification processors to avoid worker-thread tensorflow imports causing "can't register atexit after shutdown"
* don't require old password for users with admin role when changing passwords
* don't render actions menu if no options are available
* Remove hwaccel arg as it is not used for encoding
* change password button text
---------
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* ensure audio events display timeline entries in tracking details
* tweak tracking details layout for small desktop sizes
* update transcription docs
* Update classification docs for training recommendations
* Make number of classification images to be kept configurable
* Add bird to classification reference
* Fix incorrect averaging of the segments so it correctly only uses the most recent segments
* fix trigger logic
* add ability to download clean snapshot
---------
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* 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
* 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>
* 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
