Convert Apple NeuralHash model for CSAM Detection to ONNX
> Neural hash generated here might be a few bits off from one generated on an iOS device. This is expected since different iOS devices generate slightly different hashes anyway. The reason is that neural networks are based on floating-point calculations. The accuracy is highly dependent on the hardware. For smaller networks it won't make any difference. But NeuralHash has 200+ layers, resulting in significant cumulative errors.<p>This is a little unexpected. I'm not sure whether this has any implication on CSAM detection as whole. Wouldn't this require Apple to add multiple versions of NeuralHash of the same image (one for each platform/hardware) into the database to counter this issue? If that is case, doesn't this in turn weak the threshold of the detection as the same image maybe match multiple times in different devices?