* 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>
* Add limit to event query for fetching latest event with specified label and camera name
* Refactor the label_thumbnail function in frigate/http.py to simplify the event_query logic and improve code readability
* 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
* only check camera status if autotracking enabled
* a more sensible sleep time
* Only check camera status if preparing for a move
* only update tracked obj position when ptz stopped
* both pantilt *and* zoom should be idle
* check more often after moving
* No need to move pan and tilt separately
* 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 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
* Add functionality to update YAML config file with PUT request in HTTP endpoint
* Refactor copying of text to clipboard with Clipboard API and fallback to document.execCommand('copy') in CameraMap.jsx file
* Update YAML file from URL query parameters in frigate/http.py and add functionality to save motion masks, zones, and object masks in CameraMap.jsx
* formatting
* fix merging fuckup
* Refactor camera zone coordinate saving to use single query parameter per zone in CameraMap.jsx
* remove unnecessary print statements in util.py
* Refactor update_yaml_file function to separate the logic for updating YAML data into a new function update_yaml().
* fix merge errors
* Refactor code to improve error handling and add dependencies to useEffect hooks
* reduce contention on frame_queue
don't check if the queue is full, just attempt to add the frame
in a non-blocking manner, and then if it fails, skip it
* don't check if the frame queue is empty, just try and get from it
* Update frigate/video.py
Co-authored-by: Blake Blackshear <blakeb@blakeshome.com>
---------
Co-authored-by: Blake Blackshear <blakeb@blakeshome.com>
* Refactored queues to use faster_fifo instead of mp.Queue
* Refactored LimitedQueue to include a counter for the number of items in the queue and updated put and get methods to use the counter
* Refactor app.py and util.py to use a custom Queue implementation called LQueue instead of the existing Queue
* Refactor put and get methods in LimitedQueue to handle queue size and blocking behavior more efficiently
* code format
* remove code from other branch (merging fuckup)
* Check ffmpeg version instead of checking for presence of BTBN_PATH
* Query ffmpeg version in s6 run script instead of subprocessing in every import
* Define LIBAVFORMAT_VERSION_MAJOR in devcontainer too
* Formatting
* Default ffmpeg version to current btbn version so unit tests pass
* Reduce framerate before downscaling
It is cheaper to drop frames and downscale those that remain than it is
to downscale all frames and then drop some of them. This is achieved
with the filter chain `-cv fps=FPS,scale=W:H`, and perhaps was the
original intention. The plain `-r` and `-s` flags do not execute in
order though - they each put themselves at the *end* of the filterchain,
so `-r FPS -s WxH` actually applies the scale filter first, and then the
rate filter.
This fix can halve the CPU used by the detect ffmpeg process.
* Bring back hard rate limits
* Force birdseye cameras into standard aspect ratios
* Clarify comment
* Formatting
* Actually use the calculated aspect ratio when building the layout
* Fix Y aspect
* Force canvas into known aspect ratio as well
* Save canvas size and don't recalculate
* Cache coefficients that are used for different size layouts
* Further optimize calculations to not be done multiple times
* Add audio process PID to the list of processes and log the start of the audio process
* Update audio process PID key in processes dictionary to "audioDetector" instead of "audio".
* Scale layout up to max size after it has been calculated
* Limit portrait cameras to taking up 2 rows
* Fix bug
* Fix birdsye not removing cameras once objects are no longer visible
* Fix lint
* 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>
* 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
* optimize frame-per-second calculations
FPS is never calculated over differing periods for even given
counter. By only storing timestamps within the period that is
used, we avoid having to iterate 1000 entries every time it's
re-calculated (multiple times per second). 1000 entries would
normally only be needed if something is running at 100fps. A
more common speed - anywhere from 5 to 30fps, only needs 50
to 300 entries.
This isn't a huge improvement in the grand scheme, but when motion
detection is disabled, it takes nearly as much time in a flamegraph
as actually transferring the video frame.
* fix python checks
* Load labels dynamically to include custom events and audio, do not include attribute labels
* Formatting
* Fix sorting
* Also filter tracked object list on camera page
* isort
* Don't fail before load
