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A.B.
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ThisFor a RGB format, this seems to work well enough and is trivial:

diversity_score = (abs(r1 - r2) + abs(g1 - g2) + abs(b1 - b2)) / 765.0

This will give you a score between 0.0 and 1.0. The lower, the harder it is to distinguish two colors.

It should be obvious, but for the sake of completeness: the r, g, b values must be cast to a floating point number first, and it is assumed that their maximum value is 255.

This seems to work well enough and is trivial:

diversity_score = (abs(r1 - r2) + abs(g1 - g2) + abs(b1 - b2)) / 765.0

This will give you a score between 0.0 and 1.0. The lower, the harder it is to distinguish two colors.

It should be obvious, but for the sake of completeness: the r, g, b values must be cast to a floating point number first, and it is assumed that their maximum value is 255.

For a RGB format, this seems to work well enough and is trivial:

diversity_score = (abs(r1 - r2) + abs(g1 - g2) + abs(b1 - b2)) / 765.0

This will give you a score between 0.0 and 1.0. The lower, the harder it is to distinguish two colors.

It should be obvious, but for the sake of completeness: the r, g, b values must be cast to a floating point number first, and it is assumed that their maximum value is 255.

Source Link
A.B.
A.B.
  • 181
  • 4

This seems to work well enough and is trivial:

diversity_score = (abs(r1 - r2) + abs(g1 - g2) + abs(b1 - b2)) / 765.0

This will give you a score between 0.0 and 1.0. The lower, the harder it is to distinguish two colors.

It should be obvious, but for the sake of completeness: the r, g, b values must be cast to a floating point number first, and it is assumed that their maximum value is 255.