func main() {
flag.Parse()
img, data := utils.ReadStdin()
s := quantise.LEAST
if *strategy == "MOST" {
s = quantise.MOST
}
img = quantise.Quantise(img, quantise.OctreeQuantiser{
Depth: uint8(*depth),
Size: *size,
Strategy: s,
})
utils.WriteStdout(img, data)
}
// GetPalette finds a palette of the dominant colours in an image. Various
// parameters, such as the number of dominant colours to return, are given by
// the Options.
func GetPalette(img image.Image, opts *Options) Palette {
minDistance := MIN_DISTANCE
minSaturation := MIN_SATURATION
minProminence := MIN_PROMINENCE
maxColors := MAX_COLORS
nQuantized := N_QUANTIZED
if opts != nil {
if opts.MinDistance != 0 {
minDistance = opts.MinDistance
}
if opts.MaxColors != 0 {
maxColors = opts.MaxColors
}
if opts.MinProminence != 0 {
minProminence = opts.MinProminence
}
if opts.MinSaturation != 0 {
minSaturation = opts.MinSaturation
}
if opts.NQuantized != 0 {
nQuantized = opts.NQuantized
}
}
q := quantise.OctreeQuantiser{
Depth: 6,
Size: nQuantized,
Strategy: quantise.LEAST,
}
img = quantise.Quantise(img, q)
sortedCols := countColors(img)
colors, toCanonical := aggregate(sortedCols, minDistance)
colors, bgColor := detectBackground(img, colors, toCanonical)
// keep any color which meets the minimum saturation
satColors := ColorProminences{}
for _, c := range colors {
if meetsMinSaturation(c.Value, minSaturation) {
satColors = append(satColors, c)
}
}
if bgColor != nil && !meetsMinSaturation(bgColor, minSaturation) {
bgColor = nil
} else {
if len(satColors) > 0 {
colors = satColors
} else {
// keep at least one color
colors = colors[:1]
}
}
// keep any color within 10% of the majority color
finalColors := []ColorProminence{}
for _, c := range colors {
if c.Prominence >= colors[0].Prominence*minProminence {
finalColors = append(finalColors, c)
}
}
return Palette{finalColors[:maxColors], bgColor}
}