这在MATLAB中是微不足道的(有一个hsv命令):

cmap = hsv(number_of_colors)

这个问题出现在相当多的SO讨论中:

生成独特颜色的算法 生成独特的颜色 在图形中生成明显不同的RGB颜色 如何为任意自然数n生成n种不同的颜色?

提出了不同的解决方案，但没有一个是最优的。幸运的是，科学来拯救我们

任意N

彩色显示分类图像(免费下载) 一个个性化地图着色的网络服务(免费下载，一个网络服务解决方案应该在下个月可用) 选择高对比度颜色集的算法(作者提供了一个免费的c++实现) 高对比度的颜色集(问题的第一个算法)

最后两本将通过大多数大学图书馆/代理免费提供。

N是有限且相对较小的

在这种情况下，可以使用列表解决方案。关于这个主题，有一篇非常有趣的文章是免费的:

《彩色字母表和彩色编码的局限性》

有几个颜色列表可以考虑:

Boynton列出了11种几乎不会被混淆的颜色(可在前一节的第一篇论文中找到) Kelly的22种最大对比度的颜色(可以在上面的论文中找到)

我还遇到了一个麻省理工学院学生的这个调色板。 最后，下面的链接在不同颜色系统/坐标之间的转换可能是有用的(例如，文章中的一些颜色没有在RGB中指定):

http://chem8.org/uch/space-55036-do-blog-id-5333.html https://metacpan.org/pod/Color::Library::Dictionary::NBS_ISCC 色彩理论:如何将孟塞尔HVC转换为RGB/HSB/HSL

对于Kelly和Boynton的列表，我已经将其转换为RGB(除了白色和黑色，这应该很明显)。一些c#代码:

public static ReadOnlyCollection<Color> KellysMaxContrastSet
{
    get { return _kellysMaxContrastSet.AsReadOnly(); }
}

private static readonly List<Color> _kellysMaxContrastSet = new List<Color>
{
    UIntToColor(0xFFFFB300), //Vivid Yellow
    UIntToColor(0xFF803E75), //Strong Purple
    UIntToColor(0xFFFF6800), //Vivid Orange
    UIntToColor(0xFFA6BDD7), //Very Light Blue
    UIntToColor(0xFFC10020), //Vivid Red
    UIntToColor(0xFFCEA262), //Grayish Yellow
    UIntToColor(0xFF817066), //Medium Gray

    //The following will not be good for people with defective color vision
    UIntToColor(0xFF007D34), //Vivid Green
    UIntToColor(0xFFF6768E), //Strong Purplish Pink
    UIntToColor(0xFF00538A), //Strong Blue
    UIntToColor(0xFFFF7A5C), //Strong Yellowish Pink
    UIntToColor(0xFF53377A), //Strong Violet
    UIntToColor(0xFFFF8E00), //Vivid Orange Yellow
    UIntToColor(0xFFB32851), //Strong Purplish Red
    UIntToColor(0xFFF4C800), //Vivid Greenish Yellow
    UIntToColor(0xFF7F180D), //Strong Reddish Brown
    UIntToColor(0xFF93AA00), //Vivid Yellowish Green
    UIntToColor(0xFF593315), //Deep Yellowish Brown
    UIntToColor(0xFFF13A13), //Vivid Reddish Orange
    UIntToColor(0xFF232C16), //Dark Olive Green
};

public static ReadOnlyCollection<Color> BoyntonOptimized
{
    get { return _boyntonOptimized.AsReadOnly(); }
}

private static readonly List<Color> _boyntonOptimized = new List<Color>
{
    Color.FromArgb(0, 0, 255),      //Blue
    Color.FromArgb(255, 0, 0),      //Red
    Color.FromArgb(0, 255, 0),      //Green
    Color.FromArgb(255, 255, 0),    //Yellow
    Color.FromArgb(255, 0, 255),    //Magenta
    Color.FromArgb(255, 128, 128),  //Pink
    Color.FromArgb(128, 128, 128),  //Gray
    Color.FromArgb(128, 0, 0),      //Brown
    Color.FromArgb(255, 128, 0),    //Orange
};

static public Color UIntToColor(uint color)
{
    var a = (byte)(color >> 24);
    var r = (byte)(color >> 16);
    var g = (byte)(color >> 8);
    var b = (byte)(color >> 0);
    return Color.FromArgb(a, r, g, b);
}

下面是十六进制和每通道8位的RGB值:

kelly_colors_hex = [
    0xFFB300, # Vivid Yellow
    0x803E75, # Strong Purple
    0xFF6800, # Vivid Orange
    0xA6BDD7, # Very Light Blue
    0xC10020, # Vivid Red
    0xCEA262, # Grayish Yellow
    0x817066, # Medium Gray

    # The following don't work well for people with defective color vision
    0x007D34, # Vivid Green
    0xF6768E, # Strong Purplish Pink
    0x00538A, # Strong Blue
    0xFF7A5C, # Strong Yellowish Pink
    0x53377A, # Strong Violet
    0xFF8E00, # Vivid Orange Yellow
    0xB32851, # Strong Purplish Red
    0xF4C800, # Vivid Greenish Yellow
    0x7F180D, # Strong Reddish Brown
    0x93AA00, # Vivid Yellowish Green
    0x593315, # Deep Yellowish Brown
    0xF13A13, # Vivid Reddish Orange
    0x232C16, # Dark Olive Green
    ]

kelly_colors = dict(vivid_yellow=(255, 179, 0),
                    strong_purple=(128, 62, 117),
                    vivid_orange=(255, 104, 0),
                    very_light_blue=(166, 189, 215),
                    vivid_red=(193, 0, 32),
                    grayish_yellow=(206, 162, 98),
                    medium_gray=(129, 112, 102),

                    # these aren't good for people with defective color vision:
                    vivid_green=(0, 125, 52),
                    strong_purplish_pink=(246, 118, 142),
                    strong_blue=(0, 83, 138),
                    strong_yellowish_pink=(255, 122, 92),
                    strong_violet=(83, 55, 122),
                    vivid_orange_yellow=(255, 142, 0),
                    strong_purplish_red=(179, 40, 81),
                    vivid_greenish_yellow=(244, 200, 0),
                    strong_reddish_brown=(127, 24, 13),
                    vivid_yellowish_green=(147, 170, 0),
                    deep_yellowish_brown=(89, 51, 21),
                    vivid_reddish_orange=(241, 58, 19),
                    dark_olive_green=(35, 44, 22))

对于所有Java开发人员，以下是JavaFX的颜色:

// Don't forget to import javafx.scene.paint.Color;

private static final Color[] KELLY_COLORS = {
    Color.web("0xFFB300"),    // Vivid Yellow
    Color.web("0x803E75"),    // Strong Purple
    Color.web("0xFF6800"),    // Vivid Orange
    Color.web("0xA6BDD7"),    // Very Light Blue
    Color.web("0xC10020"),    // Vivid Red
    Color.web("0xCEA262"),    // Grayish Yellow
    Color.web("0x817066"),    // Medium Gray

    Color.web("0x007D34"),    // Vivid Green
    Color.web("0xF6768E"),    // Strong Purplish Pink
    Color.web("0x00538A"),    // Strong Blue
    Color.web("0xFF7A5C"),    // Strong Yellowish Pink
    Color.web("0x53377A"),    // Strong Violet
    Color.web("0xFF8E00"),    // Vivid Orange Yellow
    Color.web("0xB32851"),    // Strong Purplish Red
    Color.web("0xF4C800"),    // Vivid Greenish Yellow
    Color.web("0x7F180D"),    // Strong Reddish Brown
    Color.web("0x93AA00"),    // Vivid Yellowish Green
    Color.web("0x593315"),    // Deep Yellowish Brown
    Color.web("0xF13A13"),    // Vivid Reddish Orange
    Color.web("0x232C16"),    // Dark Olive Green
};

以下是根据上面的顺序未排序的凯利颜色。

以下是按色调排序的方凯利颜色(注意一些黄色的对比不是很明显)

就像Uri Cohen的答案，但它是一个生成器。首先要把颜色分开。确定的。

样品，左边颜色先:

#!/usr/bin/env python3
from typing import Iterable, Tuple
import colorsys
import itertools
from fractions import Fraction
from pprint import pprint

def zenos_dichotomy() -> Iterable[Fraction]:
    """
    http://en.wikipedia.org/wiki/1/2_%2B_1/4_%2B_1/8_%2B_1/16_%2B_%C2%B7_%C2%B7_%C2%B7
    """
    for k in itertools.count():
        yield Fraction(1,2**k)

def fracs() -> Iterable[Fraction]:
    """
    [Fraction(0, 1), Fraction(1, 2), Fraction(1, 4), Fraction(3, 4), Fraction(1, 8), Fraction(3, 8), Fraction(5, 8), Fraction(7, 8), Fraction(1, 16), Fraction(3, 16), ...]
    [0.0, 0.5, 0.25, 0.75, 0.125, 0.375, 0.625, 0.875, 0.0625, 0.1875, ...]
    """
    yield Fraction(0)
    for k in zenos_dichotomy():
        i = k.denominator # [1,2,4,8,16,...]
        for j in range(1,i,2):
            yield Fraction(j,i)

# can be used for the v in hsv to map linear values 0..1 to something that looks equidistant
# bias = lambda x: (math.sqrt(x/3)/Fraction(2,3)+Fraction(1,3))/Fraction(6,5)

HSVTuple = Tuple[Fraction, Fraction, Fraction]
RGBTuple = Tuple[float, float, float]

def hue_to_tones(h: Fraction) -> Iterable[HSVTuple]:
    for s in [Fraction(6,10)]: # optionally use range
        for v in [Fraction(8,10),Fraction(5,10)]: # could use range too
            yield (h, s, v) # use bias for v here if you use range

def hsv_to_rgb(x: HSVTuple) -> RGBTuple:
    return colorsys.hsv_to_rgb(*map(float, x))

flatten = itertools.chain.from_iterable

def hsvs() -> Iterable[HSVTuple]:
    return flatten(map(hue_to_tones, fracs()))

def rgbs() -> Iterable[RGBTuple]:
    return map(hsv_to_rgb, hsvs())

def rgb_to_css(x: RGBTuple) -> str:
    uint8tuple = map(lambda y: int(y*255), x)
    return "rgb({},{},{})".format(*uint8tuple)

def css_colors() -> Iterable[str]:
    return map(rgb_to_css, rgbs())

if __name__ == "__main__":
    # sample 100 colors in css format
    sample_colors = list(itertools.islice(css_colors(), 100))
    pprint(sample_colors)

每个人似乎都忽略了非常有用的YUV颜色空间的存在，它被设计用来表示人类视觉系统中可感知的颜色差异。YUV中的距离代表人类感知的差异。我需要这个功能的MagicCube4D实现4维魔方和无限数量的其他4D扭曲谜题有任意数量的脸。

我的解决方案首先在YUV中选择随机点，然后迭代分解最接近的两个点，在返回结果时只转换为RGB。方法是O(n^3)，但对于小数字或可以缓存的数字来说，这并不重要。它当然可以变得更有效，但结果似乎很好。

该函数允许亮度阈值的可选规范，以不产生任何成分比给定量更亮或更暗的颜色。IE，你可能不希望值接近黑色或白色。当产生的颜色将被用作基础色，然后通过光照、分层、透明度等进行阴影处理，并且必须仍然与基础色不同时，这是有用的。

import java.awt.Color;
import java.util.Random;

/**
 * Contains a method to generate N visually distinct colors and helper methods.
 * 
 * @author Melinda Green
 */
public class ColorUtils {
    private ColorUtils() {} // To disallow instantiation.
    private final static float
        U_OFF = .436f,
        V_OFF = .615f;
    private static final long RAND_SEED = 0;
    private static Random rand = new Random(RAND_SEED);    

    /*
     * Returns an array of ncolors RGB triplets such that each is as unique from the rest as possible
     * and each color has at least one component greater than minComponent and one less than maxComponent.
     * Use min == 1 and max == 0 to include the full RGB color range.
     * 
     * Warning: O N^2 algorithm blows up fast for more than 100 colors.
     */
    public static Color[] generateVisuallyDistinctColors(int ncolors, float minComponent, float maxComponent) {
        rand.setSeed(RAND_SEED); // So that we get consistent results for each combination of inputs

        float[][] yuv = new float[ncolors][3];

        // initialize array with random colors
        for(int got = 0; got < ncolors;) {
            System.arraycopy(randYUVinRGBRange(minComponent, maxComponent), 0, yuv[got++], 0, 3);
        }
        // continually break up the worst-fit color pair until we get tired of searching
        for(int c = 0; c < ncolors * 1000; c++) {
            float worst = 8888;
            int worstID = 0;
            for(int i = 1; i < yuv.length; i++) {
                for(int j = 0; j < i; j++) {
                    float dist = sqrdist(yuv[i], yuv[j]);
                    if(dist < worst) {
                        worst = dist;
                        worstID = i;
                    }
                }
            }
            float[] best = randYUVBetterThan(worst, minComponent, maxComponent, yuv);
            if(best == null)
                break;
            else
                yuv[worstID] = best;
        }

        Color[] rgbs = new Color[yuv.length];
        for(int i = 0; i < yuv.length; i++) {
            float[] rgb = new float[3];
            yuv2rgb(yuv[i][0], yuv[i][1], yuv[i][2], rgb);
            rgbs[i] = new Color(rgb[0], rgb[1], rgb[2]);
            //System.out.println(rgb[i][0] + "\t" + rgb[i][1] + "\t" + rgb[i][2]);
        }

        return rgbs;
    }

    public static void hsv2rgb(float h, float s, float v, float[] rgb) {
        // H is given on [0->6] or -1. S and V are given on [0->1]. 
        // RGB are each returned on [0->1]. 
        float m, n, f;
        int i;

        float[] hsv = new float[3];

        hsv[0] = h;
        hsv[1] = s;
        hsv[2] = v;
        System.out.println("H: " + h + " S: " + s + " V:" + v);
        if(hsv[0] == -1) {
            rgb[0] = rgb[1] = rgb[2] = hsv[2];
            return;
        }
        i = (int) (Math.floor(hsv[0]));
        f = hsv[0] - i;
        if(i % 2 == 0)
            f = 1 - f; // if i is even 
        m = hsv[2] * (1 - hsv[1]);
        n = hsv[2] * (1 - hsv[1] * f);
        switch(i) {
            case 6:
            case 0:
                rgb[0] = hsv[2];
                rgb[1] = n;
                rgb[2] = m;
                break;
            case 1:
                rgb[0] = n;
                rgb[1] = hsv[2];
                rgb[2] = m;
                break;
            case 2:
                rgb[0] = m;
                rgb[1] = hsv[2];
                rgb[2] = n;
                break;
            case 3:
                rgb[0] = m;
                rgb[1] = n;
                rgb[2] = hsv[2];
                break;
            case 4:
                rgb[0] = n;
                rgb[1] = m;
                rgb[2] = hsv[2];
                break;
            case 5:
                rgb[0] = hsv[2];
                rgb[1] = m;
                rgb[2] = n;
                break;
        }
    }


    // From http://en.wikipedia.org/wiki/YUV#Mathematical_derivations_and_formulas
    public static void yuv2rgb(float y, float u, float v, float[] rgb) {
        rgb[0] = 1 * y + 0 * u + 1.13983f * v;
        rgb[1] = 1 * y + -.39465f * u + -.58060f * v;
        rgb[2] = 1 * y + 2.03211f * u + 0 * v;
    }

    public static void rgb2yuv(float r, float g, float b, float[] yuv) {
        yuv[0] = .299f * r + .587f * g + .114f * b;
        yuv[1] = -.14713f * r + -.28886f * g + .436f * b;
        yuv[2] = .615f * r + -.51499f * g + -.10001f * b;
    }

    private static float[] randYUVinRGBRange(float minComponent, float maxComponent) {
        while(true) {
            float y = rand.nextFloat(); // * YFRAC + 1-YFRAC);
            float u = rand.nextFloat() * 2 * U_OFF - U_OFF;
            float v = rand.nextFloat() * 2 * V_OFF - V_OFF;
            float[] rgb = new float[3];
            yuv2rgb(y, u, v, rgb);
            float r = rgb[0], g = rgb[1], b = rgb[2];
            if(0 <= r && r <= 1 &&
                0 <= g && g <= 1 &&
                0 <= b && b <= 1 &&
                (r > minComponent || g > minComponent || b > minComponent) && // don't want all dark components
                (r < maxComponent || g < maxComponent || b < maxComponent)) // don't want all light components

                return new float[]{y, u, v};
        }
    }

    private static float sqrdist(float[] a, float[] b) {
        float sum = 0;
        for(int i = 0; i < a.length; i++) {
            float diff = a[i] - b[i];
            sum += diff * diff;
        }
        return sum;
    }

    private static double worstFit(Color[] colors) {
        float worst = 8888;
        float[] a = new float[3], b = new float[3];
        for(int i = 1; i < colors.length; i++) {
            colors[i].getColorComponents(a);
            for(int j = 0; j < i; j++) {
                colors[j].getColorComponents(b);
                float dist = sqrdist(a, b);
                if(dist < worst) {
                    worst = dist;
                }
            }
        }
        return Math.sqrt(worst);
    }

    private static float[] randYUVBetterThan(float bestDistSqrd, float minComponent, float maxComponent, float[][] in) {
        for(int attempt = 1; attempt < 100 * in.length; attempt++) {
            float[] candidate = randYUVinRGBRange(minComponent, maxComponent);
            boolean good = true;
            for(int i = 0; i < in.length; i++)
                if(sqrdist(candidate, in[i]) < bestDistSqrd)
                    good = false;
            if(good)
                return candidate;
        }
        return null; // after a bunch of passes, couldn't find a candidate that beat the best.
    }


    /**
     * Simple example program.
     */
    public static void main(String[] args) {
        final int ncolors = 10;
        Color[] colors = generateVisuallyDistinctColors(ncolors, .8f, .3f);
        for(int i = 0; i < colors.length; i++) {
            System.out.println(colors[i].toString());
        }
        System.out.println("Worst fit color = " + worstFit(colors));
    }

}

对于Python用户来说，seaborn非常简洁:

>>> import seaborn as sns
>>> sns.color_palette(n_colors=4)

它返回RGB元组列表:

[(0.12156862745098039, 0.4666666666666667, 0.7058823529411765),
(1.0, 0.4980392156862745, 0.054901960784313725),
(0.17254901960784313, 0.6274509803921569, 0.17254901960784313),
(0.8392156862745098, 0.15294117647058825, 0.1568627450980392)]

我有个主意。想象一个HSV气缸

定义亮度和饱和度的上限和下限。这在空间内定义了一个正方形的横截面环。

现在，在这个空间中随机散布N个点。

然后对它们应用迭代排斥算法，要么迭代次数固定，要么直到这些点稳定下来。

现在你应该有N个点，代表N种颜色，它们在你感兴趣的颜色空间中尽可能不同。

Hugo