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Simplify color extraction code using bandunfold
(#30869)
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1 changed files with 12 additions and 23 deletions
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@ -116,35 +116,24 @@ module Paperclip
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# The number of occurrences of a color (r, g, b) is thus encoded in band `b` at pixel position `(r, g)`
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histogram = image.hist_find_ndim(bins: BINS)
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# `histogram.max` returns an array of maxima with their pixel positions, but we don't know in which
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# band they are
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# With `bandunfold`, we get back to a (BINS*BINS)×BINS 2D image with a single band.
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# The number of occurrences of a color (r, g, b) is thus encoded at pixel position `(r * BINS + b, g)`
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histogram = histogram.bandunfold
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_, colors = histogram.max(size: 10, out_array: true, x_array: true, y_array: true)
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colors['out_array'].zip(colors['x_array'], colors['y_array']).map do |v, x, y|
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rgb_from_xyv(histogram, x, y, v)
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end.flatten.reverse.uniq
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colors['x_array'].zip(colors['y_array']).map do |x, y|
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rgb_from_hist_xy(x, y)
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end.flatten.reverse
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end
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# rubocop:disable Naming/MethodParameterName
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def rgb_from_xyv(image, x, y, v)
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pixel = image.getpoint(x, y)
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# As we only have the first 2 dimensions for this maximum, we
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# can't distinguish with different maxima with the same `r` and `g`
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# values but different `b` values.
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#
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# Therefore, we return an array of maxima, which is always non-empty,
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# but may contain multiple colors with the same values.
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pixel.filter_map.with_index do |pv, z|
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next if pv != v
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r = (x + 0.5) * 256 / BINS
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def rgb_from_hist_xy(x, y)
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r = ((x / BINS) + 0.5) * 256 / BINS
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g = (y + 0.5) * 256 / BINS
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b = (z + 0.5) * 256 / BINS
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b = ((x % BINS) + 0.5) * 256 / BINS
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ColorDiff::Color::RGB.new(r, g, b)
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end
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end
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def w3c_contrast(color1, color2)
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luminance1 = (color1.to_xyz.y * 0.01) + 0.05
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