This is all while for inference. The mean and std are the imagenet values (3 channels). The mean normalization is performed using transform_param. The scale seems to take only 1 value instead of 3 values, is there a workaround for scale taking 3 values? One idea was to divide the weights of the first convolution by the 3 values one per channel dimension (3X3X3) but I am not able to figure out how to do this? Thought someone would have already faced the same issue and had some workaround.
Hello all,
This is all while for inference. The mean and std are the imagenet values (3 channels). The mean normalization is performed using transform_param. The scale seems to take only 1 value instead of 3 values, is there a workaround for scale taking 3 values? One idea was to divide the weights of the first convolution by the 3 values one per channel dimension (3X3X3) but I am not able to figure out how to do this? Thought someone would have already faced the same issue and had some workaround.
Thanks and Regards, Srinadh.