opencv colors

"""
在利用python进行画图时，我们可能常常用的颜色就是'k'黑色,'r'红色,'b'蓝色,'g'绿色等，这些颜色分别代表常见的
几种颜色。但是当我们画图比较多时，颜色如何分配呢？可以参考下面的这些方案。
这样在画图时，可以选用的就很多，当然在应用时，如果想让你的图更有对比性，可以将对比性差的
去掉不用。
下面的代码来自matplotlib官方。
====================
List of named colors
====================

This plots a list of the named colors supported in matplotlib. Note that
:ref:`xkcd colors <xkcd-colors>` are supported as well, but are not listed here
for brevity.

For more information on colors in matplotlib see

* the :doc:`/tutorials/colors/colors` tutorial;
* the `matplotlib.colors` API;
* the :doc:`/gallery/color/color_demo`.
"""

from matplotlib.patches import Rectangle
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors


def plot_colortable(colors, title, sort_colors=True, emptycols=0):

    cell_width = 212
    cell_height = 22
    swatch_width = 48
    margin = 12
    topmargin = 40

    # Sort colors by hue, saturation, value and name.
    if sort_colors is True:
        by_hsv = sorted((tuple(mcolors.rgb_to_hsv(mcolors.to_rgb(color))),
                         name)
                        for name, color in colors.items())
        names = [name for hsv, name in by_hsv]
    else:
        names = list(colors)

    n = len(names)
    print (n)
    print (names)
    ncols = 4 - emptycols
    nrows = n // ncols + int(n % ncols > 0)

    width = cell_width * 4 + 2 * margin
    height = cell_height * nrows + margin + topmargin
    dpi = 72

    fig, ax = plt.subplots(figsize=(width / dpi, height / dpi), dpi=dpi)
    fig.subplots_adjust(margin/width, margin/height,
                        (width-margin)/width, (height-topmargin)/height)
    ax.set_xlim(0, cell_width * 4)
    ax.set_ylim(cell_height * (nrows-0.5), -cell_height/2.)
    ax.yaxis.set_visible(False)
    ax.xaxis.set_visible(False)
    ax.set_axis_off()
    ax.set_title(title, fontsize=24, loc="left", pad=10)

    for i, name in enumerate(names):
        row = i % nrows
        col = i // nrows
        y = row * cell_height

        swatch_start_x = cell_width * col
        text_pos_x = cell_width * col + swatch_width + 7

        ax.text(text_pos_x, y, name, fontsize=14,
                horizontalalignment='left',
                verticalalignment='center')

        ax.add_patch(
            Rectangle(xy=(swatch_start_x, y-9), width=swatch_width,
                      height=18, facecolor=colors[name], edgecolor='0.7')
        )

    return fig

plot_colortable(mcolors.BASE_COLORS, "Base Colors",
                sort_colors=False, emptycols=1)
plot_colortable(mcolors.TABLEAU_COLORS, "Tableau Palette",
                sort_colors=False, emptycols=2)

# sphinx_gallery_thumbnail_number = 3
plot_colortable(mcolors.CSS4_COLORS, "CSS Colors")

# Optionally plot the XKCD colors (Caution: will produce large figure)
# xkcd_fig = plot_colortable(mcolors.XKCD_COLORS, "XKCD Colors")
# xkcd_fig.savefig("XKCD_Colors.png")

plt.show()


#############################################################################
#
# .. admonition:: References
#
#    The use of the following functions, methods, classes and modules is shown
#    in this example:
#
#    - `matplotlib.colors`
#    - `matplotlib.colors.rgb_to_hsv`
#    - `matplotlib.colors.to_rgba`
#    - `matplotlib.figure.Figure.get_size_inches`
#    - `matplotlib.figure.Figure.subplots_adjust`
#    - `matplotlib.axes.Axes.text`
#    - `matplotlib.patches.Rectangle`