is there any particular reason to implement the bounding box priors as a layer in the keras model? if i'm reading this correctly, it only ever gets used again during post-processing of the prediction. is it to 'auto-configure' the priors based on input size etc... by detecting input from previous layer?
is there any particular reason to implement the bounding box priors as a layer in the keras model? if i'm reading this correctly, it only ever gets used again during post-processing of the prediction. is it to 'auto-configure' the priors based on input size etc... by detecting input from previous layer?
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