opencv colors

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""" 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`