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52ba582e54
Adds a community-supported hardware detector for the Qualcomm Hexagon NPU on QCS6490 SoCs (e.g. Radxa Dragon Q6A) via QAIRT 2.37.1 / qai_appbuilder. Mirrors the existing community-board pattern (Rockchip / Synaptics): - frigate/detectors/plugins/qnn.py: detector plugin using yolo-generic model type, lazy SDK import, runs pre-compiled QNN context binaries from Qualcomm AI Hub. - docker/qcs6490/: Dockerfile (two-stage; rebuilds qai_appbuilder wheel inside Frigate's image to match libstdc++ ABI), bake target (qcs6490.hcl), make targets (qcs6490.mk), and a host-side user_installation.sh that installs fastrpc, the QCS6490 firmware (cDSP image + skel libs), and configures cdsprpcd. - .github/workflows/ci.yml: qcs6490_build job mirroring synaptics_build. - CODEOWNERS: /docker/qcs6490/ + qnn.py. - docs: new "Qualcomm Hexagon NPU" sections under Community Supported Detectors in object_detectors.md, plus matching entries in installation.md and hardware.md. Performance on Radxa Dragon Q6A (Hexagon v68, ~12 TOPS), YOLOv8n 640x640: ~10ms per inference under light load, ~24ms with 5 RTSP cameras live. Closes #18602. |
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| DISCUSSION_TEMPLATE | ||
| ISSUE_TEMPLATE | ||
| workflows | ||
| copilot-instructions.md | ||
| dependabot.yml | ||
| FUNDING.yml | ||
| pull_request_template.md | ||