* 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
* 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
* Send mqtt message when audio is detected
* Fix value
* Add audio topics to mqtt docs and add mqtt headers
* Use existing standard for values
* Update mqtt.md
* Add auto configuration for height, width and fps in detect role
* Add auto-configuration for detect width, height, and fps for input roles with detect in the CameraConfig class in config.py
* Refactor code to retrieve video properties from input stream in CameraConfig class and add optional parameter to retrieve video duration in get_video_properties function
* format
* Set default detect dimensions to 1280x720 and update DetectConfig to use the defaults
* Revert "Set default detect dimensions to 1280x720 and update DetectConfig to use the defaults"
This reverts commit a1aed0414d.
* Add default detect dimensions if autoconfiguration failed and log a warning message
* fix warn message spelling on frigate/config.py
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* Ensure detect height and width are not None before using them in camera configuration
* docs: initial commit
* rename streamInfo to stream_info
Co-authored-by: Blake Blackshear <blakeb@blakeshome.com>
* Apply suggestions from code review
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* Update docs
* handle case then get_video_properties returns 0x0 dimension
* Set detect resolution based on stream properties if available, else apply default values
* Update FrigateConfig to set default values for stream_info if resolution detection fails
* Update camera detection dimensions based on stream information if available
---------
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
Co-authored-by: Blake Blackshear <blakeb@blakeshome.com>
* Support setting sub label scores via API
* Update docs
* Update docs
* Formatting
* Throw error when score is outside expected bounds
* Fix / cleanup
* much improved motion estimation and tracking
* docs updates
* move ptz specific mp values to ptz_metrics dict
* only check if moving at frame time
* pass full dict instead of individual values
* Basic functionality
* Threaded motion estimator
* Revert "Threaded motion estimator"
This reverts commit 3171801607.
* Don't detect motion when ptz is moving
* fix motion logic
* fix mypy error
* Add threaded queue for movement for slower ptzs
* Move queues per camera
* Move autotracker start to app.py
* iou value for tracked object
* mqtt callback
* tracked object should be initially motionless
* only draw thicker box if autotracking is enabled
* Init if enabled when initially disabled in config
* Fix init
* Thread names
* Always use motion estimator
* docs
* clarify fov support
* remove size ratio
* use mp event instead of value for ptz status
* update autotrack at half fps
* fix merge conflict
* fix event type for mypy
* clean up
* Clean up
* remove unused code
* merge conflict fix
* docs: update link to object_detectors page
* Update docs/docs/configuration/autotracking.md
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* clarify wording
* pass actual instances directly
* default return preset
* fix type
* Error message when onvif init fails
* disable autotracking if onvif init fails
* disable autotracking if onvif init fails
* ptz module
* verify required_zones in config
* update util after dev merge
---------
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* Update ha_network_storage.md to make it clear which config file
* Update docs/docs/guides/ha_network_storage.md with relative url
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
---------
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* 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>
* Clean up docs given HA addon storage support
* Add guide for using HA network storage
* Add to sidebar
* Specify that media type needs to be used
* Link to storage guide from install docs
* Instruct users to store DB in /config
* Update ha_network_storage.md
* Recommend that data is moved or deleted
* use a different method for blur and contrast to reduce CPU
* blur with radius instead
* use faster interpolation for motion
* improve contrast based on averages
* increase default threshold to 30
* ensure mask is applied after contrast improvement
* update opencv
* update benchmark script
* configurable ffmpeg timeout
* configurable ffmpeg healthcheck interval
rename timeout to healthcheck_interval
only grab config value once
* configurable ffmpeg retry interval
rename healthcheck_interval to retry_interval
* add retry_interval to docs
- update retry_interval text in config.py
* pass attribute labels as attributes
* add label attrs to events and snapshots
* incorporate area of license_plate and face into snapshot selection
* populate sublabels for cars with logos
* Update faqs.md
I spent hours trying to figure this out and if this could be included in some way that would potentially help someone out there.
* Update docs/docs/troubleshooting/faqs.md
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* Update docs/docs/troubleshooting/faqs.md
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* Update faqs.md
---------
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
Co-authored-by: Blake Blackshear <blakeb@blakeshome.com>
* refactor existing motion detector
* implement and use cnt bgsub
* pass fps to motion detector
* create a simplified motion detector
* lightning detection
* update default motion config
* lint imports
* use estimated boxes for regions
* use improved motion detector
* update test
* use a different strategy for clustering motion and object boxes
* increase alpha during calibration
* simplify object consolidation
* add some reasonable constraints to the estimated box
* adjust cluster boundary to 10%
* refactor
* add disabled debug code
* fix variable scope
