我正在开发一个项目，作为一个起点，以确定某些点的颜色，为此，我正在绘制这些图像的RGB颜色的三维图形。通过这个我已经确定了这些斑点的一些显著的颜色，如下所示。在

色彩是一种感知和主观解释的问题。这一步的目的是识别，这样你就可以找到一个没有不同解释的颜色模式。有了这个，我一直在互联网上搜索，为此，建议使用color space L * a * b *。在

有了这个，有人能帮我从颜色实验室得到这张图吗，或者指出另一种方法来更好地分类这些斑点的颜色？在

用于绘制三维图形的代码import numpy as np

import mpl_toolkits.mplot3d.axes3d as p3

import matplotlib.pyplot as plt

import colorsys

from PIL import Image

# (1) Import the file to be analyzed!

img_file = Image.open("IMD405.png")

img = img_file.load()

# (2) Get image width & height in pixels

[xs, ys] = img_file.size

max_intensity = 100

hues = {}

# (3) Examine each pixel in the image file

for x in xrange(0, xs):

for y in xrange(0, ys):

# (4) Get the RGB color of the pixel

[r, g, b] = img[x, y]

# (5) Normalize pixel color values

r /= 255.0

g /= 255.0

b /= 255.0

# (6) Convert RGB color to HSV

[h, s, v] = colorsys.rgb_to_hsv(r, g, b)

# (7) Marginalize s; count how many pixels have matching (h, v)

if h not in hues:

hues[h] = {}

if v not in hues[h]:

hues[h][v] = 1

else:

if hues[h][v] < max_intensity:

hues[h][v] += 1

# (8) Decompose the hues object into a set of one dimensional arrays we can use with matplotlib

h_ = []

v_ = []

i = []

colours = []

for h in hues:

for v in hues[h]:

h_.append(h)

v_.append(v)

i.append(hues[h][v])

[r, g, b] = colorsys.hsv_to_rgb(h, 1, v)

colours.append([r, g, b])

# (9) Plot the graph!

fig = plt.figure()

ax = p3.Axes3D(fig)

ax.scatter(h_, v_, i, s=5, c=colours, lw=0)

ax.set_xlabel('Hue')

ax.set_ylabel('Value')

ax.set_zlabel('Intensity')

fig.add_axes(ax)

plt.savefig('plot-IMD405.png')

plt.show()