All users expect the returned value to be the full model size, not the
half size. The effect of this bug was to increase the number of regions
that must be detected, reduce the context provided to the detector for
each, and force most regions to have to be scaled up, which became a CPU
bottleneck.
Setting cache-to=compression=zstd causes the resulting user-pulled image
to have zstd-compressed layers, which are not compatible with docker
prior to 23.0. Ubuntu 20.04 still ships with docker 20.10, which yields
`Error processing tar file` when pulling these images.
Renaming the jetpack cache images is my way of clearing the cache of the
prior zstd layers, and it clarifies the convention I used for the other
cache images in which there is one cache per base image/job, not per
target/step. We don't need to delete the non-jetson cache images because
they haven't been rebuilt since zstd was enabled.
* fixup! Split independent builds into parallel jobs
* Combine caches within steps of same job
* Remove Maintain Cache workflow
Now that we're caching to ghcr instead of gha, we don't have to worry
about gha's cache eviction after 7 days/10 GB.
* Factor out common setup steps
* Re-order
* Split independent builds into parallel jobs
* Cache jetson builds
* Use zstd compression
* Switch from gha cache to registry cache
A CI run (four images cached with mode-max) populates the cache with 295
cache entries totalling 23.44 GB. This exceeds gha's 10GB limit, causing
trashing. Try with a registry instead.
* Enable manual CI runs
* 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
* 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
* 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
* 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
* Refactor event label and sub-label score display in Events.jsx to include the event label and sub-label percentage
* Revert "Refactor event label and sub-label score display in Events.jsx to include the event label and sub-label percentage"
This reverts commit 87c23adf1e.
* Refactor event label and sub label score display in Events component
* 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
