6 Commits

Include renames

Author	SHA1	Message	Date
3 people	af0ba19196	Feat/deepx npu detector (#24336) ... * feat(deepx): add DEEPX NPU detector and runtime integration. * feat(deepx): enforce model_format requirement when ppu is enabled and add integrity checks for driver installation * Update frigate/detectors/plugins/deepx.py Public method lacks docstring Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * Refactor DEEPX detector tests, support SSD and DAMO-YOLO * feat(deepx): add anchor-free output decoding and corresponding tests * Add tests and updates for DEEPX detector and refactor DEEPX accelerator code structure. * fix: enhance model type validation and update documentation for DEEPX detector * fix: add support for customizable score and NMS thresholds * refactor: infer YOLO layout from the model, drop per-detector options and the dxrtd placeholder * fix: keep only the anchor-free PPU verdict, re-read anchor-based each frame * Update latency data for DEEPX NPU * Expanding PPU support for DEEPX and set yolo-generic as default. * enhance scale count resolution logic * Extend PPU layout handling and YOLOX support to DEEPX detector * fix: assume the largest PPU anchor table when the .dxnn has no layout * Improve PPU decoding and introduce strides handling * Improve PPU scope and fix box format mismatch * Fix unnamed node issue that breaks traversal * fix: update object detection model type description to remove outdated architecture --------- Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>	2026-09-21 07:50:44 -05:00
3 people	4a35573210	Initial support for Hailo-8L (#12431) ... * 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. --------- Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com> Co-authored-by: Josh Hawkins <32435876+hawkeye217@users.noreply.github.com>	2024-08-29 20:19:50 -06:00
3 people	44d8cdbba1	AMD GPU support with the rocm detector and YOLOv8 pretrained model download (#9762) ... * ROCm AMD/GPU based build and detector, WIP * detectors/rocm: separate yolov8 postprocessing into own function; fix box scaling; use cv2.dnn.blobForImage for preprocessing; assert on required model parameters * AMD/ROCm: add couple of more ultralytics models; comments * docker/rocm: make imported model files readable by all * docker/rocm: readme about running on AMD GPUs * docker/rocm: updated README * docker/rocm: updated README * docker/rocm: updated README * detectors/rocm: separated preprocessing functions into yolo_utils.py * detector/plugins: added onnx cpu plugin * docker/rocm: updated container with limite label sets * example detectors view * docker/rocm: updated README.md * docker/rocm: update README.md * docker/rocm: do not set HSA_OVERRIDE_GFX_VERSION at all for the general version as the empty value broke rocm * detectors: simplified/optimized yolov8_postprocess * detector/yolo_utils: indentation, remove unused variable * detectors/rocm: default option to conserve cpu usage at the expense of latency * detectors/yolo_utils: use nms to prefilter overlapping boxes if too many detected * detectors/edgetpu_tfl: add support for yolov8 * util/download_models: script to download yolov8 model files * docker/main: add download-models overlay into s6 startup * detectors/rocm: assume models are in /config/model_cache/yolov8/ * docker/rocm: compile onnx files into mxr files at startup * switch model download into bash script * detectors/rocm: automatically override HSA_OVERRIDE_GFX_VERSION for couple of known chipsets * docs: rocm detector first notes * typos * describe builds (harakas temporary) * docker/rocm: also build a version for gfx1100 * docker/rocm: use cp instead of tar * docker.rocm: remove README as it is now in detector config * frigate/detectors: renamed yolov8_preprocess->preprocess, pass input tensor element type * docker/main: use newer openvino (2023.3.0) * detectors: implement class aggregation * update yolov8 model * add openvino/yolov8 support for label aggregation * docker: remove pointless s6/timeout-up files * Revert "detectors: implement class aggregation" This reverts commit dcfe6bbf6f. * detectors/openvino: remove class aggregation * detectors: increase yolov8 postprocessing score trershold to 0.5 * docker/rocm: separate rocm distributed files into its own build stage * Update object_detectors.md * updated CODEOWNERS file for rocm * updated build names for documentation * Revert "docker/main: use newer openvino (2023.3.0)" This reverts commit dee95de908. * reverrted openvino detector * reverted edgetpu detector * scratched rocm docs from any mention of edgetpu or openvino * Update docs/docs/configuration/object_detectors.md Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com> * renamed frigate.detectors.yolo_utils.py -> frigate.detectors.util.py * clarified rocm example performance * Improved wording and clarified text * Mentioned rocm detector for AMD GPUs * applied ruff formating * applied ruff suggested fixes * docker/rocm: fix missing argument resulting in larger docker image sizes * docs/configuration/object_detectors: fix links to yolov8 release files --------- Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>	2024-02-10 06:41:46 -06:00
4 people	090294e89b	Initial support for rockchip boards (#8382) ... * initial support for rockchip boards * Apply suggestions from code review apply requested changes Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com> * requested changes * rewrite dockerfile * adjust targets * Update .github/workflows/ci.yml Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com> * Update docs/docs/configuration/object_detectors.md Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com> * Update docs/docs/configuration/object_detectors.md Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com> * add information to docs * Update docs/docs/configuration/object_detectors.md Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com> * format rknn.py * apply changes from isort and ruff --------- Co-authored-by: MarcA711 <> Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>	2023-11-02 12:55:24 +00:00
Andrew ReiterandGitHub	7d3e5c9c4c	Revert numpy upgrade (#7341) ... * Revert numpy upgrade * Upgrade arm64 onnx version to match amd64 * Increase CODEOWNERS granularity Not sure if it has an effect since I don't have repository write access	2023-07-31 21:45:50 -05:00
Andrew ReiterandGitHub	a96a951e23	Nvidia Jetson ffmpeg + TensorRT support (#6458) ... * 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	2023-07-26 05:50:41 -05:00