* [Init] Initial commit for Synaptics SL1680 NPU
* add a rough detector which is testing with yolov8 tflite model.
* [Feat] Add dependencies installation in docker build
- Add runtime library and wheels installation in main/Dockerfile
- Add model.synap(default model, transfer from mobilenet_224full80) in docker/synap1680
* [Update] Remove dependencies installation from main Dockerfile
- remove deps installation from Dockerfile
- add dependencies installation and split wheels, deps stage in synap1680 Dockerfile
* Refactor synap detector to more closely match other implementations
* [Update] Add model path configuration check
* [Update] update ModelType to ssd
* [Update] Remove unuse script
- install_deps.sh has already been executing in deps download stage
- Dockerfile.toolchain is for testing to extract runtime libraries from Synaptics toolchain
* [Update] update Synaptics SL1680 setup description
* [Update] remove install_synap1680
- The deps download and installation is existed in synap1680
* [Fix] update document content
* [Update] Update detector from synap1680 to synaptics
This update is in order to make the synaptics SL-series NPU detector more general.
- Fix detector `os` module not import bug
- Update detector type `synap1680` to `synaptics`
- Update document description `SL1680` to `Synaptics` only
- Update docker build content `synap1680` to `synaptics`
* [Fix] Update configuration document
* Update docs/docs/configuration/object_detectors.md
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* [Update] Update document content and detector default layout
- Update object_detectors document
- Update detector's default layout
- Update default model name
* [Update] Update object detector document content
* [Fix] Fix InputTensorEnum not defined error
- import InputTensorEnum from detector_config
* [Update] Update detector script coding format
* [Update] Update synaptics detector coding format
* [Update] Add synaptics ci workflow
* [Update] update synaptics runtime libs download path
- Fork Synaptics astra sdk repo and put the runtime lib package on it
- Frigate team can update this download path later
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Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* Don't support tensorrt detector for amd64 builds
* Add logs for directing users not to use tensorrt detector
* Rework docs
* Fix dockerfile index
* Don't undo jetson fix
* Only check if an object is stationary to avoid mqtt snapshot
* docs heading tweak
* Add more API descriptions
* Add missing lib for new rocm onnxruntime whl
* Update inference times to reflect better rocm performance
* Cleanup resetting tracked object activity
* remove print
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Co-authored-by: Josh Hawkins <32435876+hawkeye217@users.noreply.github.com>
* Catch error and show toast when failing to delete review items
* i18n keys
* add link to speed estimation docs in zone edit pane
* Implement reset of tracked object update for each camera
* Cleanup
* register mqtt callbacks for toggling alerts and detections
* clarify snapshots docs
* clarify semantic search reindexing
* add ukrainian
* adjust date granularity for last recording time
The api endpoint only returns granularity down to the day
* Add amd hardware
* fix crash in face library on initial start after enabling
* Fix recordings view for mobile landscape
The events view incorrectly was displaying two columns on landscape view and it only took up 20% of the screen width. Additionally, in landscape view the timeline was too wide (especially on iPads of various screen sizes) and would overlap the main video
* face rec overfitting instructions
* Clarify
* face docs
* clarify
* clarify
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Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* Adding Models
* Final Async Update
* Bug Fixing
* Fix
* Adding fixes
* Working async infer
* Final Documenatation and debug update
* Removing some extra prints
* Post-process correct label push
* config docs fix
* Review Fix
* Review fix 2.0
* Fixing the ASYNC API to work from 30ms to 10ms
* Fix for multi stream async infernce
* Format
* Fix#3
* Format#2
* Remove Unnessery includes
* Sort Imports
* Refactor hardware docs to show model specific speeds
* Move hailo to first party detectors
* Make note of multiple detectors
* Improve hierarchy
* Update object_detectors.md
* Update hardware.md
* Implement ROCm detectors
* Cleanup tensor input
* Fixup image creation
* Add support for yolonas in onnx
* Get build working with onnx
* Update docs and simplify config
* Remove unused imports
* Initial support for Hailo-8L
Added file for Hailo-8L detector including dockerfile, h8l.mk, h8l.hcl, hailo8l.py, ci.yml and ssd_mobilenat_v1.hef as the inference network.
Added files to help with the installation of Hailo-8L dependences like generate_wheel_conf.py, requirements-wheel-h8l.txt and modified setup.py to try and work with any hardware.
Updated docs to reflect Initial Hailo-8L support including oject_detectors.md, hardware.md and installation.md.
* Update .github/workflows/ci.yml
typo h8l not arm64
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* Update docs/docs/configuration/object_detectors.md
Clarity for the end user and correct uses of words
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* Update docs/docs/frigate/installation.md
typo
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* update Installation.md to clarify Hailo-8L installation process.
* Update docs/docs/frigate/hardware.md
Co-authored-by: Josh Hawkins <32435876+hawkeye217@users.noreply.github.com>
* Update hardware.md add Inference time.
* Oops no new line at the end of the file.
* Update docs/docs/frigate/hardware.md typo
Co-authored-by: Josh Hawkins <32435876+hawkeye217@users.noreply.github.com>
* Update dockerfile to download the ssd_modilenet_v1 model instead of having it in the repo.
* Updated dockerfile so it dose not download the model file.
add function to download it at runtime.
update model path.
* fix formatting according to ruff and removed unnecessary functions.
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Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
Co-authored-by: Josh Hawkins <32435876+hawkeye217@users.noreply.github.com>
