lyl8213/Plate_Recognition-LPRnet

advantage of division and reduce_mean and square part layers

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Hi @lyl8213
why we use this part of the code? what's the advantage of this part?

    cx = mean(sqrt(x))
    x = Lambda(lambda x: x[0]/x[1])([x,cx]) # division

    x1 = AveragePooling2D(pool_size=[4,1],strides=[4,1],padding='same')(inputs)
    cx1 = mean(sqrt(x1))
    x1 = Lambda(lambda x: x[0]/x[1])([x1,cx1]) # division

    x2 = AveragePooling2D(pool_size=[4,1],strides=[4,1],padding='same')(x2)
    cx2 = mean(sqrt(x2))
    x2 = Lambda(lambda x: x[0]/x[1])([x2,cx2]) # division

    x3 = AveragePooling2D(pool_size=[2,1],strides=[2,1],padding='same')(x3)
    cx3 = mean(sqrt(x3))
    x3 = Lambda(lambda x: x[0]/x[1])([x3,cx3]) # division

    x = concatenate([x,x1,x2,x3], axis=3)