* 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
* Make main frigate build non rpi specific and build rpi using base image
* Add boards to sidebar
* Fix docker build
* Fix docs build
* Update pr branch for testing
* remove target from rpi build
* Remove manual build
* Add push build for rpi
* fix typos, improve wording
* Add arm build for rpi
* Cleanup and add default github ref name
* Cleanup docker build file system
* Setup to use docker bake
* Add ci/cd for bake
* Fix path
* Fix devcontainer
* Set targets
* Fix build
* Fix syntax
* Add wheels target
* Move dev container to trt
* Update key and fix rpi local
* Move requirements files and set intermediate targets
* Add back --load
* Update docs for community board development
* Update installation docs to reflect different builds available
* Update docs with official and community supported headers
* Update codeowners docs
* Update docs
* Assemble main and standard builds
* Change order of pushes
* Remove community board after successful build
* Fix rpi bake file names
* Update to latest tensorrt (8.6.1) release
* Build trt libyolo_layer.so in container
* Update tensorrt_models script to convert models from the frigate container
* Fix typo in model script
* Fix paths to yolo lib and models folder
* Add S6 scripts to test and convert specified TensortRT models at startup.
Rearrange tensorrt files into a docker support folder.
* Update TensorRT documentation to reflect the new model conversion process and minimum HW support.
* Fix model_cache path to live in config directory
* Move tensorrt s6 files to the correct directory
* Fix issues in model generation script
* Disable global timeout for s6 services
* Add version folder to tensorrt model_cache path
* Include TensorRT version 8.5.3
* Add numpy requirement prior to removal of np.bool
* This TRT version uses a mixture of cuda dependencies
* Redirect stdout from noisy model conversion
* Initial audio classification model implementation
* fix mypy
* Keep audio labelmap local
* Cleanup
* Start adding config for audio
* Add the detector
* Add audio detection process keypoints
* Build out base config
* Load labelmap correctly
* Fix config bugs
* Start audio process
* Fix startup issues
* Try to cleanup restarting
* Add ffmpeg input args
* Get audio detection working
* Save event to db
* End events if not heard for 30 seconds
* Use not heard config
* Stop ffmpeg when shutting down
* Fixes
* End events correctly
* Use api instead of event queue to save audio events
* Get events working
* Close threads when stop event is sent
* remove unused
* Only start audio process if at least one camera is enabled
* Add const for float
* Cleanup labelmap
* Add audio icon in frontend
* Add ability to toggle audio with mqtt
* Set initial audio value
* Fix audio enabling
* Close logpipe
* Isort
* Formatting
* Fix web tests
* Fix web tests
* Handle cases where args are a string
* Remove log
* Cleanup process close
* Use correct field
* Simplify if statement
* Use var for localhost
* Add audio detectors docs
* Add restream docs to mention audio detection
* Add full config docs
* Fix links to other docs
---------
Co-authored-by: Jason Hunter <hunterjm@gmail.com>
