Gate the docker/main/Dockerfile pip --ignore-installed workaround behind a
PIP_IGNORE_INSTALLED build arg that is empty for every stock image and set
only for the JP7 (Ubuntu 24.04 noble) TensorRT base. Non-JP7 images now build
a byte-identical command. Revert the ov-converter change entirely since that
stage is always debian:12, never noble.
Drop the incidental shell re-quoting in the trt-model-prepare run script,
keeping only the functional TensorRT-major-aware runtime library check
(.so.8 on JP6, .so.10 on JP7; libnvparsers removed in TRT 10).
Adds a `-tensorrt-jp7` Frigate image for JetPack 7.2 / L4T R39.2 Jetson hosts,
built on nvcr.io/nvidia/tensorrt:26.02-py3-igpu (TensorRT 10.11, CUDA 13, py3.12),
keeping the existing JP6 path unchanged. ONNX Runtime GPU is built from source
(no public aarch64 onnxruntime-gpu wheel), TensorRT-Python branch is selected by
the base image, and TensorRT runtime library checks are major-version aware.
VALIDATED on a real AGX Orin (L4T R39.2 / nv_tegra_release R39 rev 2.0):
- image frigate:test-tensorrt-jp7 builds (rc=0, 16.3GB,
sha256:c9e4d382f1603ee130ee4a7315b4f71f9461405e3785707251505e2d6d088df3)
- ONNX Runtime 1.25.1 exposes CUDAExecutionProvider, and a real Add-model
inference RAN on the iGPU CUDA EP (functional, not just listed)
- frigate.util.model.get_ort_providers(False,"AUTO") = [CUDA, CPU] (CUDA first,
CPU last, TensorRT EP excluded) -> the ONNX detector GPU-accelerates on JP7
- /etc/TENSORRT_VER = 10.11.0
Native `type: tensorrt` (.trt gen) + the ORT TensorRT EP stay DRAFT-GATED: the
L4T R39 host ships NO libnvdla_compiler.so (absent from host AND base image), so
`import tensorrt` and libonnxruntime_providers_tensorrt.so fail to load. ONNX
detector GPU acceleration is the supported JP7 path; native trt is deferred.
Build fixes the new noble/CUDA-13 base surfaced (beyond the plan):
- build_nginx.sh: enable deb-src for the deb822 ubuntu.sources (Ubuntu 24.04)
- tensorrt_libyolo.sh: strip -lnvToolsExt (removed in CUDA 13) + -lnvparsers
(dropped in TensorRT 10) when those libs are absent
- docker/main: noble/py3.12 build adjustments (Dockerfile, build_sqlite_vec.sh)
Reproducible: `make -C docker/tensorrt ... local-trt-jp7` (JETPACK7_ARGS) on any
arm64 builder; built on-device only because the GPU smoke test needs the iGPU.
* Move openai specific workaround so it doesn't apply to other providers
* Fix gemini tool calling
* Improve efficiency of frame listing for previews
* debug replay fixes
- initial selection without changing the radio button in the dialog would select 1 hour (rather than 1 minute)
- use CLIPS_DIR instead of CACHE_DIR so that longer replay clips don't cause tmpfs cache overflows
* don't re-render the tracking details overlay on every video time tick
* change pinned to planned
---------
Co-authored-by: Josh Hawkins <32435876+hawkeye217@users.noreply.github.com>
* basic e2e frontend test framework
* improve mock data generation and add test cases
* more cases
* add e2e tests to PR template
* don't generate mock data in PR CI
* satisfy codeql check
* fix flaky system page tab tests by guarding against crashes from incomplete mock stats
* reduce local test runs to 4 workers to match CI
* mobile button spacing
* prevent console warning about div being descendant of p
* ensure consistent spacing
* add missing i18n keys
* i18n fixes
- add missing translations
- fix dot notation keys
* use plain string
* add missing key
* add i18next-cli commands for extraction and status
also add false positives removal for several keys
* add i18n key check step to PR workflow
* formatting
* Add node/npm version config to package.json
* Bump npm version/fix node version format
* Version range
* Use package.json for github actions node version
* Unification
* Move it all to the bottom
* Remove this
* Bump versions in docs
* Add volta config here too
* Revert changes
* Revert this
* [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
---------
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* Install peewee type hints
* Models now have proper types
* Fix iterator type
* Enable debug builds with dev reqs installed
* Install as wheel
* Fix cast type
* Update vite
* Update LuIcons
* Update radix packages
* Fix other icons
* Use correct node version
* Remove superfluous web build on python tests
* Move web build to test
* Simplify rocm install and update to 6.3.1
* Build out more necessary packages
* Update to 6.3.3
* Set bake version
* Fix typo
* Ensure NHWC is used
* Reset dev changes
* Write to cache
* Get stats for embeddings inferences
* cleanup embeddings inferences
* Enable UI for feature metrics
* Change threshold
* Fix check
* Update python for actions
* Set python version
* Ignore type for now
* Fix access
* Reorganize tracked object for imports
* Separate out rockchip build
* Formatting
* Use original ffmpeg build
* Fix build
* Update default search type value
