def rand_cmap(nlabels, type='bright', first_color_black=True,
    last_color_black=False, verbose=True):
    """
    Creates a random colormap to be used together with matplotlib. Useful for segmentation tasks
    :param nlabels: Number of labels (size of colormap)
    :param type: 'bright' for strong colors, 'soft' for pastel colors
    :param first_color_black: Option to use first color as black, True or False
    :param last_color_black: Option to use last color as black, True or False
    :param verbose: Prints the number of labels and shows the colormap. True or False
    :return: colormap for matplotlib
    """
    from matplotlib.colors import LinearSegmentedColormap
    import colorsys
    import numpy as np
    if type not in ('bright', 'soft'):
        print('Please choose "bright" or "soft" for type')
        return
    if verbose:
        print('Number of labels: ' + str(nlabels))
    if type == 'bright':
        randHSVcolors = [(np.random.uniform(low=0.0, high=1), np.random.
            uniform(low=0.2, high=1), np.random.uniform(low=0.9, high=1)) for
            i in range(nlabels)]
        randRGBcolors = []
        for HSVcolor in randHSVcolors:
            randRGBcolors.append(colorsys.hsv_to_rgb(HSVcolor[0], HSVcolor[
                1], HSVcolor[2]))
        if first_color_black:
            randRGBcolors[0] = [0, 0, 0]
        if last_color_black:
            randRGBcolors[-1] = [0, 0, 0]
        random_colormap = LinearSegmentedColormap.from_list('new_map',
            randRGBcolors, N=nlabels)
    if type == 'soft':
        low = 0.6
        high = 0.95
        randRGBcolors = [(np.random.uniform(low=low, high=high), np.random.
            uniform(low=low, high=high), np.random.uniform(low=low, high=
            high)) for i in range(nlabels)]
        if first_color_black:
            randRGBcolors[0] = [0, 0, 0]
        if last_color_black:
            randRGBcolors[-1] = [0, 0, 0]
        random_colormap = LinearSegmentedColormap.from_list('new_map',
            randRGBcolors, N=nlabels)
    if verbose:
        from matplotlib import colors, colorbar
        from matplotlib import pyplot as plt
        fig, ax = plt.subplots(1, 1, figsize=(15, 0.5))
        bounds = np.linspace(0, nlabels, nlabels + 1)
        norm = colors.BoundaryNorm(bounds, nlabels)
        cb = colorbar.ColorbarBase(ax, cmap=random_colormap, norm=norm,
            spacing='proportional', ticks=None, boundaries=bounds, format=
            '%1i', orientation=u'horizontal')
    return random_colormap
