* 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
