[深度学习][原创]语义分割中如何将预测索图转换为对应的RGB的3通道图

Posted 2022-11-03 FL1623863129

看下面示例，其实就是很巧妙的运用了numpy切片操作

代码：

import numpy as np

COLORMAP = [
    [128, 64, 128],
    [244, 35, 232],
    [70, 70, 70],
    [102, 102, 156],
    [190, 153, 153],
    [153, 153, 153],
    [250, 170, 30],
    [220, 220, 0],
    [107, 142, 35],
    [152, 251, 152],
    [0, 130, 180],
    [220, 20, 60],
    [255, 0, 0],
    [0, 0, 142],
    [0, 0, 70],
    [0, 60, 100],
    [0, 80, 100],
    [0, 0, 230],
    [119, 11, 32],
]
a = np.array([[1, 2, 3, 4], [4, 5, 6, 7], [0, 1, 2, 3]])
print(a.shape)  # (3,4)
print(a)
colormap = np.array(COLORMAP, dtype='uint8')  # (19,3)
print(colormap.shape)
print(colormap)
c = colormap[a, :]
print(c.shape)  # (3,4,3)
print(c)

输出结果：

(3, 4)
[[1 2 3 4]
 [4 5 6 7]
 [0 1 2 3]]
(19, 3)
[[128  64 128]
 [244  35 232]
 [ 70  70  70]
 [102 102 156]
 [190 153 153]
 [153 153 153]
 [250 170  30]
 [220 220   0]
 [107 142  35]
 [152 251 152]
 [  0 130 180]
 [220  20  60]
 [255   0   0]
 [  0   0 142]
 [  0   0  70]
 [  0  60 100]
 [  0  80 100]
 [  0   0 230]
 [119  11  32]]
(3, 4, 3)
[[[244  35 232]
  [ 70  70  70]
  [102 102 156]
  [190 153 153]]

 [[190 153 153]
  [153 153 153]
  [250 170  30]
  [220 220   0]]

 [[128  64 128]
  [244  35 232]
  [ 70  70  70]
  [102 102 156]]]