brief.jl:There is an error in the range

[zhuxyu]

I think there was an error in brief.jl, the default value range of rand() is [0,1), so I think in the random_unfiorm function, rand() should be changed to (rand().-0.5) * 2

julia> brief_params = BRIEF(sampling_type = random_uniform)
BRIEF{typeof(random_uniform)}(128, 9, 1.4142135623730951, ImageFeatures.random_uniform, 123)
julia> brief_params.window      # window = 9, so the value of CartesianIndex should in [-4:4]
9
julia> B = brief_params.sampling_type(brief_params.size, brief_params.window, brief_params.seed)     # All values of the index are positive and in [0:4].
(CartesianIndex{2}[CartesianIndex(4, 3), CartesianIndex(2, 1), CartesianIndex(0, 1), CartesianIndex(2, 3), CartesianIndex(2, 1), CartesianIndex(1, 3), CartesianIndex(4, 0), CartesianIndex(4, 2), CartesianIndex(4, 1), CartesianIndex(4, 4)  …  CartesianIndex(2, 0), CartesianIndex(2, 4), CartesianIndex(1, 1), CartesianIndex(3, 4), CartesianIndex(3, 1), CartesianIndex(4, 4), CartesianIndex(1, 1), CartesianIndex(2, 3), CartesianIndex(1, 0), CartesianIndex(3, 3)], CartesianIndex{2}[CartesianIndex(1, 3), CartesianIndex(0, 2), CartesianIndex(2, 0), CartesianIndex(2, 1), CartesianIndex(1, 2), CartesianIndex(3, 1), CartesianIndex(3, 2), CartesianIndex(3, 2), CartesianIndex(0, 2), CartesianIndex(1, 2)  …  CartesianIndex(1, 2), CartesianIndex(2, 0), CartesianIndex(2, 4), CartesianIndex(1, 4), CartesianIndex(0, 2), CartesianIndex(1, 0), CartesianIndex(0, 2), CartesianIndex(4, 3), CartesianIndex(3, 1), CartesianIndex(0, 1)])

[Jay-sanjay]

so what it is showing after changing to (rand().-0.5) * 2

[Jay-sanjay]

(rand()-0.5) * 2

[mkitti]

This is the expression being considered.

        x_gen = floor(Int, window * rand() / 2)

Let's first consider the subexpression

window * rand() / 2

This will produce a pseudo random number in the range [0, window/2)

If window = 6, then the numbers will be picked fromba uniform distribution within [0,3).

Flooring this would result in the following mapping:

[0,1) -> 0
[1,2) -> 1
[2,3) -> 2

This should be essentially the same as rand(0:2)

If window = 7 then this would pick from a uniform random distribution from [0,3.5)

0,1) -> 0
[1,2) -> 1
[2,3) -> 2
[3,3.5) -> 3

This would be equivalent to rand([0,0,1,1,2,2,3]) as 3 is selected half as frequently as the other integers.

The proposal is to use (rand().-0.5) * 2 which should be equal to 2rand() - 1.0. This draws a random number from [-1,1).

If window = 6, then values [-3,3) would be sampled with the equivalent being rand(-3:2).