* don't zoom if camera doesn't support it
* basic zooming
* make zooming configurable
* zooming docs
* optional zooming in camera status
* Use absolute instead of relative zooming
* increase edge threshold
* zoom considering object area
* bugfixes
* catch onvif zooming errors
* relative zooming option for dahua/amcrest cams
* docs
* docs
* don't make small movements
* remove old logger statement
* fix small movements
* use enum in config for zooming
* fix formatting
* empty move queue first
* clear tracked object before waiting for stop
* use velocity estimation for movements
* docs updates
* add tests
* typos
* recalc every 50 moves
* adjust zoom based on estimate box if calibrated
* tweaks for fast objects and large movements
* use real time for calibration and add info logging
* docs updates
* remove area scale
* Add example video to docs
* zooming font header size the same as the others
* log an error if a ptz doesn't report a MoveStatus
* debug logging for onvif service capabilities
* ensure camera supports ONVIF MoveStatus
* Add args to ignore audio and only process keyframes
* Add timelapse args to config
* Update docs
* Formatting
* Fix spacing
* Fix formatting
* add example of math for pts
* add note about network bandwidth permissions
* Update default net int
* Set default network interfaces to empty
* Don't read interfaces if none are set
* Formatting
* Add stderr output
* Reduce database queries to necessary labels
* Set columns for other queries
* skip creating model instances
---------
Co-authored-by: Blake Blackshear <blakeb@blakeshome.com>
* Run ffmpeg sub process & video_properties as async
* Run recording cleanup in the main process
* More cleanup
* Use inter process communication to write recordings into the DB
* Formatting
* Non-Jetson changes
Required for later commits:
- Allow base image to be overridden (and don't assume its WORKDIR)
- Ensure python3.9
- Map hwaccel decode presets as strings instead of lists
Not required:
- Fix existing documentation
- Simplify hwaccel scale logic
* Prepare for multi-arch tensorrt build
* Add tensorrt images for Jetson boards
* Add Jetson ffmpeg hwaccel
* Update docs
* Add CODEOWNERS
* CI
* Change default model from yolov7-tiny-416 to yolov7-320
In my experience the tiny models perform markedly worse without being
much faster
* fixup! Update docs
* Store camera labels in dict and other optimizations
* Add max on timeout so it is at least 60
* Ensure db timeout is at least 60
* Update list once a day to ensure new labels are cleaned up
* Formatting
* Insert recordings as bulk instead of individually.
* Fix
* Refactor event and timeline cleanup
* Remove unused
