利用Python实现生成颜色表(color chart)

木子童话

前言

在做色彩相关的算法分析时候，经常需要使用规则的颜色表来进行辅助。下面用python（numpy和opencv）来生成颜色表并保存为图片。
有两种类型：

• 格子形状的颜色表
  
• 渐变色带
  

长的样子分别如下：

格子颜色表

这里需要注意，当划分的颜色数量比较少时，最好把一个颜色像素扩展成为一个格子，不然的话整个图看起来就太小了。

1. # -*- coding: utf-8 -*-
   
2. import cv2
   
3. import numpy as np
   
4. 
   
5. 
   
6. def generate_color_chart(block_num=18,
   
7.                          block_columns=6,
   
8.                          grid_width=32,
   
9.                          grid_height=None):
   
10.     """
    
11.     Generate color chart by uniformly distributed color indexes, only support
    
12.     8 bit (uint8).
    
13. 
    
14.     Parameters
    
15.     ----------
    
16.     block_num: Block number of color chart, also the number of color indexes.
    
17.     block_columns: Column number of color chart. Row number is computed by
    
18.         block_num / block_columns
    
19.     grid_width: Width of color grid
    
20.     grid_height: Height of color grid. If not set, it will equal to grid_width.
    
21.     """
    
22.     color_index = np.linspace(0, 255, block_num)
    
23.     color_index = np.uint8(np.round(color_index))
    
24. 
    
25.     if grid_height is None:
    
26.         grid_height = grid_width
    
27. 
    
28.     # compute sizes
    
29.     block_rows = np.int_(np.ceil(block_num / block_columns))
    
30.     block_width = grid_width * block_num
    
31.     block_height = grid_height * block_num
    
32.     width = block_width * block_columns
    
33.     height = block_height * block_rows
    
34.     result = np.zeros((height, width, 3), dtype=np.uint8)
    
35. 
    
36.     # compute red-green block, (blue will be combined afterward)
    
37.     red_block, green_block = np.meshgrid(color_index, color_index)
    
38.     red_block = expand_pixel_to_grid(red_block, grid_width, grid_height)
    
39.     green_block = expand_pixel_to_grid(green_block, grid_width, grid_height)
    
40.     rg_block = np.concatenate([red_block, green_block], axis=2)
    
41. 
    
42.     # combine blue channel
    
43.     for i in range(block_num):
    
44.         blue = np.ones_like(rg_block[..., 0], dtype=np.uint8) * color_index[i]
    
45.         color_block = np.concatenate([rg_block, blue[..., np.newaxis]], axis=2)
    
46.         # compute block index
    
47.         block_row = i // block_columns
    
48.         block_column = i % block_columns
    
49.         xmin = block_column * block_width
    
50.         ymin = block_row * block_height
    
51.         xmax = xmin + block_width
    
52.         ymax = ymin + block_height
    
53.         result[ymin:ymax, xmin:xmax, :] = color_block
    
54. 
    
55.     result = result[..., ::-1]  # convert from rgb to bgr
    
56.     return result
    
57. 
    
58. 
    
59. def expand_pixel_to_grid(matrix, grid_width, grid_height):
    
60.     """
    
61.     Expand a pixel to a grid. Inside the grid, every pixel have the same value
    
62.     as the source pixel.
    
63. 
    
64.     Parameters
    
65.     ----------
    
66.     matrix: 2D numpy array
    
67.     grid_width: width of grid
    
68.     grid_height: height of grid
    
69.     """
    
70.     height, width = matrix.shape[:2]
    
71.     new_heigt = height * grid_height
    
72.     new_width = width * grid_width
    
73.     repeat_num = grid_width * grid_height
    
74. 
    
75.     matrix = np.expand_dims(matrix, axis=2).repeat(repeat_num, axis=2)
    
76.     matrix = np.reshape(matrix, (height, width, grid_height, grid_width))
    
77.     # put `height` and `grid_height` axes together;
    
78.     # put `width` and `grid_width` axes together.
    
79.     matrix = np.transpose(matrix, (0, 2, 1, 3))
    
80.     matrix = np.reshape(matrix, (new_heigt, new_width, 1))
    
81.     return matrix
    
82. 
    
83. 
    
84. if __name__ == '__main__':
    
85.     color_chart16 = generate_color_chart(block_num=16,
    
86.                                          grid_width=32,
    
87.                                          block_columns=4)
    
88.     color_chart18 = generate_color_chart(block_num=18,
    
89.                                          grid_width=32,
    
90.                                          block_columns=6)
    
91.     color_chart36 = generate_color_chart(block_num=36,
    
92.                                          grid_width=16,
    
93.                                          block_columns=6)
    
94.     color_chart52 = generate_color_chart(block_num=52,
    
95.                                          grid_width=8,
    
96.                                          block_columns=13)
    
97.     color_chart256 = generate_color_chart(block_num=256,
    
98.                                           grid_width=1,
    
99.                                           block_columns=16)
    
100. 
     
101.     cv2.imwrite('color_chart16.png', color_chart16)
     
102.     cv2.imwrite('color_chart18.png', color_chart18)
     
103.     cv2.imwrite('color_chart36.png', color_chart36)
     
104.     cv2.imwrite('color_chart52.png', color_chart52)
     
105.     cv2.imwrite('color_chart256.png', color_chart256)

复制代码

渐变色带

1. # -*- coding: utf-8 -*-
   
2. import cv2
   
3. import numpy as np
   
4. 
   
5. 
   
6. def generate_color_band(left_colors, right_colors, grade=256, height=32):
   
7.     """
   
8.     Generate color bands by uniformly changing from left colors to right
   
9.     colors. Note that there might be multiple bands.
   
10. 
    
11.     Parameters
    
12.     ----------
    
13.     left_colors: Left colors of the color bands.
    
14.     right_colors: Right colors of the color bands.
    
15.     grade: how many colors are contained in one color band.
    
16.     height: height of one color band.
    
17.     """
    
18.     # check and process color parameters, which should be 2D list
    
19.     # after processing
    
20.     if not isinstance(left_colors, (tuple, list)):
    
21.         left_colors = [left_colors]
    
22.     if not isinstance(right_colors, (tuple, list)):
    
23.         right_colors = [right_colors]
    
24. 
    
25.     if not isinstance(left_colors[0], (tuple, list)):
    
26.         left_colors = [left_colors]
    
27.     if not isinstance(right_colors[0], (tuple, list)):
    
28.         right_colors = [right_colors]
    
29. 
    
30.     # initialize channel, and all other colors should have the same channel
    
31.     channel = len(left_colors[0])
    
32. 
    
33.     band_num = len(left_colors)
    
34.     result = []
    
35.     for i in range(band_num):
    
36.         left_color = left_colors[i]
    
37.         right_color = right_colors[i]
    
38.         if len(left_color) != channel or len(right_color) != channel:
    
39.             raise ValueError("All colors should have same channel number")
    
40. 
    
41.         color_band = np.linspace(left_color, right_color, grade)
    
42.         color_band = np.expand_dims(color_band, axis=0)
    
43.         color_band = np.repeat(color_band, repeats=height, axis=0)
    
44.         color_band = np.clip(np.round(color_band), 0, 255).astype(np.uint8)
    
45.         result.append(color_band)
    
46.     result = np.concatenate(result, axis=0)
    
47.     result = np.squeeze(result)
    
48.     return result
    
49. 
    
50. 
    
51. if __name__ == '__main__':
    
52.     black = [0, 0, 0]
    
53.     white = [255, 255, 255]
    
54.     red = [0, 0, 255]
    
55.     green = [0, 255, 0]
    
56.     blue = [255, 0, 0]
    
57. 
    
58.     gray_band = generate_color_band([[0], [255]], [[255], [0]])
    
59.     color_band8 = generate_color_band(
    
60.         [black, white, red, green, blue, black, black, black],
    
61.         [white, black, white, white, white, red, green, blue]
    
62.     )
    
63. 
    
64.     cv2.imwrite('gray_band.png', gray_band)
    
65.     cv2.imwrite('color_band8.png', color_band8)

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