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Add a community-supported board build for Qualcomm SoCs with a Hexagon NPU, accelerating TFLite object detection through the QNN TFLite delegate on the Hexagon Tensor Processor (HTP). Supported boards: - IQ9100 (IQ-9075 EVK) - QCS6490 (RB3 Gen 2 Vision Kit / Rubik Pi 3) - detector: new `qualcomm_tfl` plugin loading libQnnTFLiteDelegate.so on the HTP backend, reusing the shared TFLite delegate helpers - docker: `docker/qualcomm` board build (Dockerfile, qualcomm.hcl, qualcomm.mk) producing the arm64 `-qualcomm` image - cdi: per-board Container Device Interface descriptors and an install helper exposing the NPU device nodes and QNN libraries to the container - ci/codeowners: register the qualcomm build target and code owner - docs: installation, hardware, and object detector documentation, using the shared model config dropdown component - i18n: add the Qualcomm detector label and description to the generated en config locale Signed-off-by: Rami Mouro <rmouro@qti.qualcomm.com>
This is the Frigate frontend which connects to and provides a User Interface to the Python backend.
Web Development
Installing Web Dependencies Via NPM
Within /web, run:
npm install
Running development frontend
Within /web, run:
PROXY_HOST=<ip_address:port> npm run dev
The Proxy Host can point to your existing Frigate instance. Otherwise defaults to localhost:5000 if running Frigate on the same machine.
Extensions
Install these IDE extensions for an improved development experience:
- eslint