* Subclass Process for audio_process
* Introduce custom mp.Process subclass
In preparation to switch the multiprocessing startup method away from
"fork", we cannot rely on os.fork cloning the log state at fork time.
Instead, we have to set up logging before we run the business logic of
each process.
* Make camera_metrics into a class
* Make ptz_metrics into a class
* Fixed PtzMotionEstimator.ptz_metrics type annotation
* Removed pointless variables
* Do not start audio processor when no audio cameras are configured
* Moved FrigateApp.init_config() into FrigateConfig.load()
* Move frigate config loading into main
* Store PlusApi in FrigateConfig
* Register SIGTERM handler in main
* Ensure logging is setup during config parsing
* Removed pointless try
* Moved config initialization out of FrigateApp
* Made FrigateApp.shm_frame_count into a function
* Removed log calls from signal handlers
python's logging calls are not re-entrant, which caused at least one of
these to deadlock randomly.
* Reopen stdout/err on process fork
This helps avoid deadlocks (https://github.com/python/cpython/issues/91776).
* Make mypy happy
* Whoops. I might have forgotten to save.
Truly an amateur mistake.
* Always call FrigateApp.stop()
* 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)
* Add isort and ruff linter
Both linters are pretty common among modern python code bases.
The isort tool provides stable sorting and grouping, as well as pruning
of unused imports.
Ruff is a modern linter, that is very fast due to being written in rust.
It can detect many common issues in a python codebase.
Removes the pylint dev requirement, since ruff replaces it.
* treewide: fix issues detected by ruff
* treewide: fix bare except clauses
* .devcontainer: Set up isort
* treewide: optimize imports
* treewide: apply black
* treewide: make regex patterns raw strings
This is necessary for escape sequences to be properly recognized.
* dont wait so long for queues
* implement stop methods for comms
* set the detection events on exit and return early from processing
* handle the stop event in the broadcast threads
* short circuit the detection process exit code if it already exited
* some logging for stats thread
* just keep the log process alive 1 second after the last log message
* ensure the multiprocessing queues are emptied and closed
* Update frigate/log.py
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* Update frigate/log.py
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* mypy fixes
---------
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* Initial work for adding OpenVino detector. Not functional
* Load model and submit for inference.
Sucessfully load model and initialize OpenVino engine with either CPU or GPU as device.
Does not parse results for objects.
* Detection working with ssdlite_mobilenetv2 FP16 model
* Add OpenVIno support and model to docker image
* Add documentation for OpenVino detector configuration
* Adds support for ARM32/ARM64 and the Myriad X hardware
- Use custom-built openvino wheel for all platforms
- Add libusb build without udev for NCS2 support
* Add documentation around Intel CPU requirements and NCS2 setup
* Print all available output tensors
* Update documentation for config parameters
* Refactor EdgeTPU and CPU model handling to detector submodules.
* Fix selecting the correct detection device type from the config
* Remove detector type check when creating ObjectDetectProcess
* Fixes after rebasing to 0.11
* Add init file to detector folder
* Rename to detect_api
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* Add unit test for LocalObjectDetector class
* Add configuration for model inputs
Support transforming detection regions to RGB or BGR.
Support specifying the input tensor shape. The tensor shape has a standard format ["BHWC"] when handed to the detector, but can be transformed in the detector to match the model shape using the model input_tensor config.
* Add documentation for new model config parameters
* Add input tensor transpose to LocalObjectDetector
* Change the model input tensor config to use an enumeration
* Updates for model config documentation
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
