Looking in their github, it says that it uses openCV and Tensorflow. The motion detection is done with openCV and will be immune against any attack unless you move so slow that you are under the detection threshold.
Tensorflow for the object detection doesn't do any OCR thus written instructions dont work. However, according to the website the system has a limited list of objects it detects. So maybe disguising yourself as a walking tree might prevent detection.
I think the defaults are fairly sensitive. I had to add motion masks to ignore trees
In addition, if something else like a 2nd tree moves, then it will get sent to the detector which will potentially label the other thing (my trees were causing false positives because it thought the stationary fence post was a human)
With an open source model, though, a criminal may be able to work out a 2D image that he could print out that would identify him as a package or a windy branch.
the criminal could spend years to become a trusted maintainer so they can upload a model that's been fine tuned to ignore objects with a specific QR code.
Someone made a shirt called ChatGP-Tee, that had (IIRC) a picture of a generic office view, it confused the model completely and it didn't recognise the wearer as human :D
They have a two-stage approach, first motion detection with - I think - OpenCV and then afterwards object detection of zones of interest with different object detection models, depending on your hardware.
It supports Coral TPU, Halio Accelerator and most GPUs. I think AMD is still the worst, since ROCm is not available on iGPUs.
Afterwards, they provide/support models like edgedet (Coral), YOLO-NAS, YOLO, D-Fine or RF-DETR.
They also offer paid access to a specially trained version of YOLO-NAS where you can also train your own images.
Tensorflow for the object detection doesn't do any OCR thus written instructions dont work. However, according to the website the system has a limited list of objects it detects. So maybe disguising yourself as a walking tree might prevent detection.