[Beta Support]: Incorrect Face Detection with ArcFace (large) on RK3588 (Orange Pi 5) #22058
hsea
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Beta Support
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That warning is not important as it is a static shape model. It's always possible that the model is just getting it wrong for no particular reason. It's also possible that the quantization processes reduces accuracy. In my testing it did generally work correctly |
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Describe the problem you are having
I am experiencing issues with face detection and recognition when using the ArcFace (large) model on an RK3588 CPU (Orange Pi Plus 5).
Expected Behavior:
The model should correctly detect and extract faces when a person is present in the frame.
Actual Behavior:
When using the ArcFace (large) model, the system often fails to extract valid faces—either extracting non-face objects or missing faces entirely when a person is clearly visible.
In the same scenario, switching to the FaceNet (small) model works correctly, with proper face detection and extraction.
Additionally, I observed the following:
The log shows a warning:
W Query dynamic range failed. Ret code: RKNN_ERR_MODEL_INVALID. (If it is a static shape RKNN model, please ignore the above warning message.)
This warning appears even though the model runs.
Beta Version
0.17.0 Release Candidate 2
Issue Category
Object Detection / Detectors
Frigate config file
Relevant Frigate log output
Relevant go2rtc log output (if applicable)
Install method
Docker Compose
docker-compose file or Docker CLI command
Operating system
Other Linux
CPU / GPU / Hardware
Orange Pi 5 Plus 16GB (RK3588)
Screenshots
Steps to reproduce
Any other information that may be helpful
There was also an installation issue with the ArcFace model:
frigate.util.rknn_converter Error during RKNN conversion: No module named 'pkg_resources'
This was resolved by manually installing setuptools inside the Docker container, but the face detection issues persist.
uname -a
Linux OPI 6.12.41-trim #227 SMP PREEMPT Thu Feb 12 08:05:38 UTC 2026 aarch64 GNU/Linux
The issue seems specific to the ArcFace model on RK3588 hardware.
Thank you for this great project
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