Optimise colour approximations
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@ -1,5 +1,7 @@
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[deps]
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Colors = "5ae59095-9a9b-59fe-a467-6f913c188581"
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FixedPointNumbers = "53c48c17-4a7d-5ca2-90c5-79b7896eea93"
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GLMakie = "e9467ef8-e4e7-5192-8a1a-b1aee30e663a"
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Makie = "ee78f7c6-11fb-53f2-987a-cfe4a2b5a57a"
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Memoize = "c03570c3-d221-55d1-a50c-7939bbd78826"
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Observables = "510215fc-4207-5dde-b226-833fc4488ee2"
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@ -2,70 +2,18 @@ module ColourApproximations
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using Colors
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using GLMakie
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using Makie.GeometryBasics: Rect, HyperRectangle
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using Observables
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# Utilities
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const colours3bit = # xterm colours
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Colorant[colorant"rgb(0, 0, 0)",
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colorant"rgb(205, 0, 0)",
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colorant"rgb(0, 205, 0)",
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colorant"rgb(205, 205, 0)",
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colorant"rgb(0, 0, 238)",
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colorant"rgb(205, 0, 205)",
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colorant"rgb(0, 205, 205)",
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colorant"rgb(229, 229, 229)"]
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const colours4bit = # xterm again
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vcat(colours3bit,
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Colorant[colorant"rgb(127, 127, 127)",
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colorant"rgb(255, 0, 0)",
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colorant"rgb(0, 252, 0)",
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colorant"rgb(255, 255, 0)",
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colorant"rgb(0, 0, 252)",
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colorant"rgb(255, 0, 255)",
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colorant"rgb(0, 255, 255)",
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colorant"rgb(255, 255, 255)"])
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const colour6cube =
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Colorant[RGB(r, g, b)
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for r in range(0, 1, length=6)
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for g in range(0, 1, length=6)
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for b in range(0, 1, length=6)]
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const colour24greys = Colorant[RGB(w, w, w) for w in range(0, 1, length=24)]
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const colours8bit = vcat(colours4bit, colour6cube, colour24greys)
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include("coloursets.jl")
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include("pairsurrounding.jl")
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const coloursets =
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[Symbol("3-bit") => colours3bit,
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Symbol("4-bit") => colours4bit,
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Symbol("8-bit") => colours8bit]
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nearestcolour(metric::Colors.DifferenceMetric, options::Vector{<:Colorant}, colour::Colorant) =
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options[argmin(o -> colordiff(options[o], colour; metric), axes(options, 1))]
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const nearcolourcache =
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Dict{Colors.DifferenceMetric, Dict{Symbol, Dict{Colorant, Colorant}}}()
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function nearestcolour(metric::Colors.DifferenceMetric, options::Symbol)
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if !haskey(nearcolourcache, metric)
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nearcolourcache[metric] = Dict{Symbol, Dict{Colorant, Colorant}}()
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end
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if !haskey(nearcolourcache[metric], options)
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nearcolourcache[metric][options] = Dict{Colorant, Colorant}()
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end
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relevantcache = nearcolourcache[metric][options]
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colourset = coloursets[findfirst(s -> first(s) == options, coloursets)] |> last
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function (c::Colorant)
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cached = get(relevantcache, c, nothing)
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if isnothing(cached)
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cached = relevantcache[c] = nearestcolour(metric, colourset, c)
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end
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cached
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end
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end
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Symbol("8-bit") => colours8bit,
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Symbol("24-bit") => Colorant[]]
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# Extra colour differences
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@ -78,11 +26,11 @@ colour_distance_metrics =
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"CIEΔE94" => DE_94(),
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"BFD" => DE_BFD(),
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"CMC" => DE_CMC(),
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"JPC79" => DE_JPC79(),
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# "JPC79" => DE_JPC79(),
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"l2 LAB" => DE_AB(),
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"l2 DIN99" => DE_DIN99(),
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"l2 DIN99d" => DE_DIN99d(),
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"l2 DIN99o" => DE_DIN99o(),
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# "l2 DIN99d" => DE_DIN99d(),
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# "l2 DIN99o" => DE_DIN99o(),
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"l2 RGB" => DE_RGB(),
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"l2 HSL" => DE_HSL()]
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@ -90,8 +38,11 @@ colour_distance_metrics =
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saturation = Observable(1.0)
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x_granularity = Observable(256)
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y_granularity = Observable(128)
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y_granularity = Observable(256)
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x_granularity = Observable(128)
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const x_grads = round.(Int, 2 .^(sort(vcat(6:10, (6:10) .+ log2(1.5)))))
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const y_grads = round.(Int, 2 .^(sort(vcat(5:10, (5:9) .+ log2(1.5)))))
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diffmetric = Observable{Colors.DifferenceMetric}(last(first(colour_distance_metrics)))
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@ -99,44 +50,33 @@ diffmetric = Observable{Colors.DifferenceMetric}(last(first(colour_distance_metr
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fig = Figure()
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controlrow1 = fig[1,1] = GridLayout()
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xgrad_slider = Slider(controlrow1[1,2], range=32:32:1024, startvalue=x_granularity[])
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Label(controlrow1[1,1], text="X divisions")
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ygrad_slider = Slider(controlrow1[1,4], range=16:16:512, startvalue=y_granularity[])
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Label(controlrow1[1,3], text="Y divisions")
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metric_slider = Slider(controlrow1[1,6], range=1:length(colour_distance_metrics))
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Label(controlrow1[1,5], text=@lift(colour_distance_metrics[$(metric_slider.value)] |> first))
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connect!(x_granularity, xgrad_slider.value)
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connect!(y_granularity, ygrad_slider.value)
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# colsize!(controlrow1, 1, Auto(true, 0.0))
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# colsize!(controlrow1, 2, Fixed(120))
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# colsize!(controlrow1, 3, Auto(true, 0.0))
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# colsize!(controlrow1, 4, Fixed(120))
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# colsize!(controlrow1, 5, Auto(true, 0.0))
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# colsize!(controlrow1, 6, Fixed(160))
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ax = Axis(fig[2,1])
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hidedecorations!(ax)
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hidespines!(ax)
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controlrow1 = fig[1,1] = GridLayout()
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xgrad_slider = Slider(controlrow1[1,2], range=y_grads, startvalue=y_granularity[])
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Label(controlrow1[1,1], text="Y divisions")
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ygrad_slider = Slider(controlrow1[1,4], range=x_grads, startvalue=x_granularity[])
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Label(controlrow1[1,3], text="X divisions")
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metric_slider = Slider(controlrow1[1,6], range=1:length(colour_distance_metrics))
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Label(controlrow1[1,5], text=@lift(colour_distance_metrics[$(metric_slider.value)] |> first))
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connect!(y_granularity, xgrad_slider.value)
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connect!(x_granularity, ygrad_slider.value)
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controlrow2 = fig[3,1] = GridLayout()
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saturation_slider = Slider(controlrow2[1,2], range = 0:0.01:1, startvalue=saturation[])
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Label(controlrow2[1,1], text="Saturation")
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colourset_slider = Slider(controlrow2[1,4], range=1:length(coloursets))
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Label(controlrow2[1,3], text=@lift(coloursets[$(colourset_slider.value)] |> first |> string))
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round_colours = Toggle(controlrow2[1,6])
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Label(controlrow2[1,5], text="Round")
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colsize!(controlrow2, 1, Auto(true, 0.0))
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colsize!(controlrow2, 2, Auto(false, 0.8))
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colsize!(controlrow2, 3, Auto(true, 0.0))
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colsize!(controlrow2, 4, Fixed(100))
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colsize!(controlrow2, 5, Auto(true, 0.0))
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colsize!(controlrow2, 6, Fixed(60))
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colsize!(controlrow2, 4, Makie.Fixed(100))
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# Plotting
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@ -146,37 +86,32 @@ map!(diffmetric, metric_slider.value) do v
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colour_distance_metrics[v] |> last
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end
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roundfun = Observable{Function}(identity)
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map!(roundfun, diffmetric, colourset_slider.value) do metric, cset
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nearestcolour(metric, coloursets[cset] |> first)
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end
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rect_list = Observable(Vector{HyperRectangle}())
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rect_list = map(x_granularity, y_granularity) do x, y
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[Rect(i, j, 1, 1) for i in 1:x for j in 1:y]
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end
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colour_list_unprocessed = map(saturation) do s
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colour_grid_unprocessed = map(y_granularity, x_granularity, saturation) do x, y, s
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[HSL(h, s, l)
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for h in range(0, 360, length=x_granularity[])
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for l in range(0, 1, length=y_granularity[])]
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for h in range(0, 360, length=x),
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l in range(0, 1, length=y)]
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end
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colour_list = Observable(Vector{Colorant}())
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map!(colour_list, colour_list_unprocessed, roundfun, round_colours.active) do clist, cround, croundp
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if croundp cround.(clist) else clist end
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colour_grid = Observable(Matrix{Colorant}(undef, 0, 0))
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map!(colour_grid, colour_grid_unprocessed, diffmetric, colourset_slider.value) #=
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=# do cmat, metric, cset
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if cset == length(coloursets)
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cmat
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else
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growcolours(metric, last(coloursets[cset]), cmat)
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end
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end
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# The main event
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p = poly!(ax, rect_list, color = colour_list)
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image!(ax, colour_grid)
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on(rect_list, priority=1) do
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delete!(ax, p)
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p = poly!(ax, rect_list, color = colour_list)
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on(y_granularity, priority=-1) do _
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reset_limits!(ax)
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end
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fig
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on(x_granularity, priority=-1) do _
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reset_limits!(ax)
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end
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end
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@ -0,0 +1,33 @@
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using Colors
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using FixedPointNumbers
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const colours3bit = # xterm colours
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[colorant"rgb(0, 0, 0)",
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colorant"rgb(205, 0, 0)",
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colorant"rgb(0, 205, 0)",
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colorant"rgb(205, 205, 0)",
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colorant"rgb(0, 0, 238)",
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colorant"rgb(205, 0, 205)",
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colorant"rgb(0, 205, 205)",
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colorant"rgb(229, 229, 229)"]
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const colours4bit = # xterm again
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vcat(colours3bit,
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[colorant"rgb(127, 127, 127)",
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colorant"rgb(255, 0, 0)",
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colorant"rgb(0, 252, 0)",
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colorant"rgb(255, 255, 0)",
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colorant"rgb(0, 0, 252)",
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colorant"rgb(255, 0, 255)",
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colorant"rgb(0, 255, 255)",
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colorant"rgb(255, 255, 255)"])
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const colour6cube =
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[RGB{N0f8}(r, g, b)
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for r in range(0, 1, length=6)
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for g in range(0, 1, length=6)
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for b in range(0, 1, length=6)]
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const colour24greys = [RGB{N0f8}(w, w, w) for w in range(0, 1, length=24)]
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const colours8bit = vcat(colours4bit, colour6cube, colour24greys)
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@ -0,0 +1,126 @@
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using Colors
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using StatsBase
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using FixedPointNumbers: N0f8, Normed
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using Memoize
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StatsBase.pairwise(metric::Colors.DifferenceMetric, colours::Vector{<:Colorant}) =
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pairwise((x, y) -> colordiff(x, y; metric), colours)
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function colourdistances(metric::Colors.DifferenceMetric, colours::Vector{<:Colorant})
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distmat = pairwise(metric, colours)
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Dict(c => sort([distmat[i, j] => colours[j]
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for j in setdiff(axes(distmat, 1), i)],
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by=first)
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for (i, c) in enumerate(colours))
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end
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function deconstruct(colour::C) where {C <: Colorant}
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fnames = fieldnames(C)
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getfield.(colour, fnames)
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end
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deconstruct(colour::RGB{N0f8}) =
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Float64.(getfield.(colour, (:r, :g, :b)))
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function construct(C::Type{<:Colorant}, fields::Tuple)
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eval(Expr(:new, C, fields...))
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end
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construct(::Type{RGB{N0f8}}, fields::NTuple{3, Float64}) =
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RGB{N0f8}(fields...)
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@memoize nearestcolour(metric::Colors.DifferenceMetric, options::Vector{<:Colorant}, colour::Colorant) =
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options[argmin(o -> colordiff(options[o], colour; metric), axes(options, 1))]
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"""
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Examine various mixings of colours `a` and `b` in an attempt to confirm whether
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there are no other colours from `options` that lie directly between `a` and `b`
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according to `metric`.
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This is done by bisecting the mix factor and checking if any other colours are
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reported as nearest within `tol` of the crossover point.
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"""
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function bisectadjacency(metric::Colors.DifferenceMetric, a::C, b::C, options::Vector{<:Colorant}; tol=1e-6) where {C <: Colorant}
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af, bf, = deconstruct.((a, b))
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lastmixfactor, mixfactor, mixstep = 1.0, 0.5, 0.25
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while abs(lastmixfactor - mixfactor) > tol
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abf = @. mixfactor * af + (1 - mixfactor) * bf
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ab = construct(C, abf)
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near_ab = nearestcolour(metric, options, ab)
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if near_ab == a
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lastmixfactor, mixfactor = mixfactor, mixfactor + mixstep
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elseif near_ab == b
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lastmixfactor, mixfactor = mixfactor, mixfactor - mixstep
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else
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return false
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end
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mixstep /= 2
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end
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return true
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end
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function adjacentcolours(metric::Colors.DifferenceMetric, colours::Vector{C}) where {C <: Colorant}
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distlist = colourdistances(metric, colours) |> collect
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adjacencylist = Dict{C, Vector{Pair{Float64, C}}}()
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for (c, others) in distlist
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adjacencylist[c] =
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filter(oth -> let o = last(oth)
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if haskey(adjacencylist, o)
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c ∈ last.(adjacencylist[o])
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else
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bisectadjacency(metric, c, o, colours)
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end
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end, others)
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end
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adjacencylist
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end
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@memoize function growcolours(metric::Colors.DifferenceMetric, colours::Vector{<:Colorant},
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refmat::Matrix{<:Colorant})
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cmat = Matrix{Union{Colorant, Missing}}(fill(missing, size(refmat)))
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cadj = adjacentcolours(metric, colours)
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for i in CartesianIndices(cmat)
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if ismissing(cmat[i])
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# @info "@ $(i.I)"
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cnearest = nearestcolour(metric, colours, refmat[i])
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cmat[i] = cnearest
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if length(cadj[cnearest]) > 0
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safethreshold = minimum(first.(cadj[cnearest]))/2
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growcolour!(cmat, metric, refmat, cnearest, safethreshold, i)
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end
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end
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end
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Matrix{Colorant}(cmat)
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end
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function growcolour!(cmat::Matrix{Union{Colorant, Missing}}, metric::Colors.DifferenceMetric,
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refmat::Matrix{<:Colorant}, cnearest::Colorant, safethreshold::Float64,
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pos::CartesianIndex{2})
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# @info "Growing $(pos.I)"
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surrounding = Ref(pos) .+ CartesianIndex{2}.([(0, 1), (0, -1), (1, 0), (-1, 0)])
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filter!(s -> all((1,1) .<= s.I .<= size(refmat)), surrounding)
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reseed = Vector{CartesianIndex{2}}()
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for spos in surrounding
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# @info " @ $(spos.I)"
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if ismissing(cmat[spos]) && colordiff(cnearest, refmat[spos]; metric) < safethreshold
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cmat[spos] = cnearest
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push!(reseed, spos)
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end
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end
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for spos in reseed
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growcolour!(cmat, metric, refmat, cnearest, safethreshold, spos)
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end
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end
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function colour_grid_hsl(xs, ys, saturation=1)
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[HSL(h, saturation, l)
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for h in range(0, 360, length=xs),
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l in range(0, 1, length=ys)]
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end
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# function growcolours!(cmat::Matrix, metric::Colors.DifferenceMetric,
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# adjc::Dict{Colorant, Vector{Pair{Float64, Colorant}}}, refmat::Matrix,
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# pos::CartesianIndex{2},
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# lrwrap::Bool=false, udwrap::Bool=false)
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# end
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