Wrong. Most facial recognition software reduces largest image dimension to 128. This allows caching to become effective, massively speeds up the process (hence the 15k fps).

A facial recognition pipeline contains a few steps, for feature extraction people DO resize image to something like 128x128, but for face detection (which is what this repo does) you DON'T.

Also, the reason why we scale down the input image is not for cache effectiveness, it's simply for reducing computations needed. Maybe except for naive matrix multiplication and convolution implementations, which is what this repo does. But there is no point to discuss performance if you are using a naive implementation which by design ignores cache/instruction latency/anything Computer Architecture related. Please, at least take QNNPACK as baseline.