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Miscellaneous fixes (#23661)

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* update face recognition docs

* clarify

* improve faq grouping

* add faqitem component

* add enable http link for reolinks

* update plus docs

* update autotracking faq

* fix typos
This commit is contained in:
Josh Hawkins
2026-07-10 07:09:15 -06:00
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parent 20c2be4368
commit f6596ac7b0
22 changed files with 437 additions and 75 deletions
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docs/docs/configuration/object_detectors.md
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@@ -725,7 +725,7 @@ The inference time was determined on a rk3588 with 3 NPU cores.
To convert a onnx model to the rknn format using the [rknn-toolkit2](https://github.com/airockchip/rknn-toolkit2/) you have to:
- Place one ore more models in onnx format in the directory `config/model_cache/rknn_cache/onnx` on your docker host (this might require `sudo` privileges).
- Place one or more models in onnx format in the directory `config/model_cache/rknn_cache/onnx` on your docker host (this might require `sudo` privileges).
- Save the configuration file under `config/conv2rknn.yaml` (see below for details).
- Run `docker exec <frigate_container_id> python3 /opt/conv2rknn.py`. If the conversion was successful, the rknn models will be placed in `config/model_cache/rknn_cache`.