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Add support for object detection on Rubik Pi 3 (#2005)

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Sam Freund
2025-08-09 10:02:55 -05:00
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# Orange Pi 5 (and variants) Object Detection
## How it works
PhotonVision runs object detection on the Orange Pi 5 by use of the RKNN model architecture, and [this JNI code](https://github.com/PhotonVision/rknn_jni).
## Supported models
PhotonVision currently ONLY supports 640x640 Ultralytics YOLOv5, YOLOv8, and YOLOv11 models trained and converted to `.rknn` format for RK3588 SOCs! Other models require different post-processing code and will NOT work.
## Converting Custom Models
:::{warning}
Only quantized models are supported, so take care when exporting to select the option for quantization.
:::
PhotonVision now ships with a [Python Notebook](https://github.com/PhotonVision/photonvision/blob/main/scripts/rknn-convert-tool/rknn_conversion.ipynb) that you can use in [Google Colab](https://colab.research.google.com) or in a local environment. In Google Colab, you can simply paste the PhotonVision GitHub URL into the "GitHub" tab and select the `rknn_conversion.ipynb` notebook without needing to manually download anything.
Please ensure that the model you are attempting to convert is among the {ref}`supported models <docs/objectDetection/opi:Supported Models>` and using the PyTorch format.