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利用Python实现生成颜色表(colorchart)

来源:互联网 收集:自由互联 发布时间:2023-07-07
目录 前言 格子颜色表 渐变色带 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
目录
  • 前言
  • 格子颜色表
  • 渐变色带

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。

# -*- coding: utf-8 -*-
import cv2
import numpy as np


def generate_color_chart(block_num=18,
                         block_columns=6,
                         grid_width=32,
                         grid_height=None):
    """
    Generate color chart by uniformly distributed color indexes, only support
    8 bit (uint8).

    Parameters
    ----------
    block_num: Block number of color chart, also the number of color indexes.
    block_columns: Column number of color chart. Row number is computed by
        block_num / block_columns
    grid_width: Width of color grid
    grid_height: Height of color grid. If not set, it will equal to grid_width.
    """
    color_index = np.linspace(0, 255, block_num)
    color_index = np.uint8(np.round(color_index))

    if grid_height is None:
        grid_height = grid_width

    # compute sizes
    block_rows = np.int_(np.ceil(block_num / block_columns))
    block_width = grid_width * block_num
    block_height = grid_height * block_num
    width = block_width * block_columns
    height = block_height * block_rows
    result = np.zeros((height, width, 3), dtype=np.uint8)

    # compute red-green block, (blue will be combined afterward)
    red_block, green_block = np.meshgrid(color_index, color_index)
    red_block = expand_pixel_to_grid(red_block, grid_width, grid_height)
    green_block = expand_pixel_to_grid(green_block, grid_width, grid_height)
    rg_block = np.concatenate([red_block, green_block], axis=2)

    # combine blue channel
    for i in range(block_num):
        blue = np.ones_like(rg_block[..., 0], dtype=np.uint8) * color_index[i]
        color_block = np.concatenate([rg_block, blue[..., np.newaxis]], axis=2)
        # compute block index
        block_row = i // block_columns
        block_column = i % block_columns
        xmin = block_column * block_width
        ymin = block_row * block_height
        xmax = xmin + block_width
        ymax = ymin + block_height
        result[ymin:ymax, xmin:xmax, :] = color_block

    result = result[..., ::-1]  # convert from rgb to bgr
    return result


def expand_pixel_to_grid(matrix, grid_width, grid_height):
    """
    Expand a pixel to a grid. Inside the grid, every pixel have the same value
    as the source pixel.

    Parameters
    ----------
    matrix: 2D numpy array
    grid_width: width of grid
    grid_height: height of grid
    """
    height, width = matrix.shape[:2]
    new_heigt = height * grid_height
    new_width = width * grid_width
    repeat_num = grid_width * grid_height

    matrix = np.expand_dims(matrix, axis=2).repeat(repeat_num, axis=2)
    matrix = np.reshape(matrix, (height, width, grid_height, grid_width))
    # put `height` and `grid_height` axes together;
    # put `width` and `grid_width` axes together.
    matrix = np.transpose(matrix, (0, 2, 1, 3))
    matrix = np.reshape(matrix, (new_heigt, new_width, 1))
    return matrix


if __name__ == '__main__':
    color_chart16 = generate_color_chart(block_num=16,
                                         grid_width=32,
                                         block_columns=4)
    color_chart18 = generate_color_chart(block_num=18,
                                         grid_width=32,
                                         block_columns=6)
    color_chart36 = generate_color_chart(block_num=36,
                                         grid_width=16,
                                         block_columns=6)
    color_chart52 = generate_color_chart(block_num=52,
                                         grid_width=8,
                                         block_columns=13)
    color_chart256 = generate_color_chart(block_num=256,
                                          grid_width=1,
                                          block_columns=16)

    cv2.imwrite('color_chart16.png', color_chart16)
    cv2.imwrite('color_chart18.png', color_chart18)
    cv2.imwrite('color_chart36.png', color_chart36)
    cv2.imwrite('color_chart52.png', color_chart52)
    cv2.imwrite('color_chart256.png', color_chart256)

渐变色带
# -*- coding: utf-8 -*-
import cv2
import numpy as np


def generate_color_band(left_colors, right_colors, grade=256, height=32):
    """
    Generate color bands by uniformly changing from left colors to right
    colors. Note that there might be multiple bands.

    Parameters
    ----------
    left_colors: Left colors of the color bands.
    right_colors: Right colors of the color bands.
    grade: how many colors are contained in one color band.
    height: height of one color band.
    """
    # check and process color parameters, which should be 2D list
    # after processing
    if not isinstance(left_colors, (tuple, list)):
        left_colors = [left_colors]
    if not isinstance(right_colors, (tuple, list)):
        right_colors = [right_colors]

    if not isinstance(left_colors[0], (tuple, list)):
        left_colors = [left_colors]
    if not isinstance(right_colors[0], (tuple, list)):
        right_colors = [right_colors]

    # initialize channel, and all other colors should have the same channel
    channel = len(left_colors[0])

    band_num = len(left_colors)
    result = []
    for i in range(band_num):
        left_color = left_colors[i]
        right_color = right_colors[i]
        if len(left_color) != channel or len(right_color) != channel:
            raise ValueError("All colors should have same channel number")

        color_band = np.linspace(left_color, right_color, grade)
        color_band = np.expand_dims(color_band, axis=0)
        color_band = np.repeat(color_band, repeats=height, axis=0)
        color_band = np.clip(np.round(color_band), 0, 255).astype(np.uint8)
        result.append(color_band)
    result = np.concatenate(result, axis=0)
    result = np.squeeze(result)
    return result


if __name__ == '__main__':
    black = [0, 0, 0]
    white = [255, 255, 255]
    red = [0, 0, 255]
    green = [0, 255, 0]
    blue = [255, 0, 0]

    gray_band = generate_color_band([[0], [255]], [[255], [0]])
    color_band8 = generate_color_band(
        [black, white, red, green, blue, black, black, black],
        [white, black, white, white, white, red, green, blue]
    )

    cv2.imwrite('gray_band.png', gray_band)
    cv2.imwrite('color_band8.png', color_band8)

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