在numpy数组中映射值

palette = np.array( [ [0,0,0], # black
... [255,0,0], # red

... [0,255,0], # green
... [0,0,255], # blue
... [255,255,255] ] ) # white

image = np.array( [ [ 0, 1, 2, 0 ], # each value corresponds to a color in the palette

... [ 0, 3, 4, 0 ] ] )

palette[image] # the (2,4,3) color image

array([[[ 0, 0, 0],

    [255,   0,   0],
    [  0, 255,   0],
    [  0,   0,   0]],
   [[  0,   0,   0],
    [  0,   0, 255],
    [255, 255, 255],
    [  0,   0,   0]]])

您可能想要考虑结构化数组，因为它允许没有数据类型的元组object。

import numpy as np

replacements = {-1: (255, 0, 0), 0: (0, 255, 0), 1: (0, 0, 255)}

arr = np.array([[ 1, 0, -1],

            [-1,  1,  1],
            [ 0,  0,  1]])

new = np.zeros(arr.shape, dtype=np.dtype([('r', np.int32), ('g', np.int32), ('b', np.int32)]))

for n, tup in replacements.items():

new[arr == n] = tup

print(new)
输出：

[[( 0, 0, 255) ( 0, 255, 0) (255, 0, 0)]
[(255, 0, 0) ( 0, 0, 255) ( 0, 0, 255)]
[( 0, 255, 0) ( 0, 255, 0) ( 0, 0, 255)]]
另一个选择是使用3D数组，其中最后一个维度是3。第一个“层”是红色，第二个“层”是绿色，第三个“层”是蓝色。此选项与plt.imshow()。兼容。

import numpy as np

arr = np.array([[ 1, 0, -1],

            [-1,  1,  1],
            [ 0,  0,  1]])

new = np.zeros((*arr.shape, 3))

for i in range(-1, 2):

new[i + 1, arr == i] = 255

输出：

array([[[ 0., 0., 255.],

    [255.,   0.,   0.],
    [  0.,   0.,   0.]],

   [[  0., 255.,   0.],
    [  0.,   0.,   0.],
    [255., 255.,   0.]],

   [[255.,   0.,   0.],
    [  0., 255., 255.],
    [  0.,   0., 255.]]])