def getpallete(num_cls):
    """
    this function is to get the colormap for visualizing the segmentation mask
    :param num_cls: the number of visulized class
    :return: the pallete
    """
    n = num_cls
    pallete_raw = np.zeros((n, 3)).astype('uint8')
    pallete = np.zeros((n, 3)).astype('uint8')

    pallete_raw[6, :] =  [111,  74,   0]
    pallete_raw[7, :] =  [ 81,   0,  81]
    pallete_raw[8, :] =  [128,  64, 128]
    pallete_raw[9, :] =  [244,  35, 232]
    pallete_raw[10, :] =  [250, 170, 160]
    pallete_raw[11, :] = [230, 150, 140]
    pallete_raw[12, :] = [ 70,  70,  70]
    pallete_raw[13, :] = [102, 102, 156]
    pallete_raw[14, :] = [190, 153, 153]
    pallete_raw[15, :] = [180, 165, 180]
    pallete_raw[16, :] = [150, 100, 100]
    pallete_raw[17, :] = [150, 120,  90]
    pallete_raw[18, :] = [153, 153, 153]
    pallete_raw[19, :] = [153, 153, 153]
    pallete_raw[20, :] = [250, 170,  30]
    pallete_raw[21, :] = [220, 220,   0]
    pallete_raw[22, :] = [107, 142,  35]
    pallete_raw[23, :] = [152, 251, 152]
    pallete_raw[24, :] = [ 70, 130, 180]
    pallete_raw[25, :] = [220,  20,  60]
    pallete_raw[26, :] = [255,   0,   0]
    pallete_raw[27, :] = [  0,   0, 142]
    pallete_raw[28, :] = [  0,   0,  70]
    pallete_raw[29, :] = [  0,  60, 100]
    pallete_raw[30, :] = [  0,   0,  90]
    pallete_raw[31, :] = [  0,   0, 110]
    pallete_raw[32, :] = [  0,  80, 100]
    pallete_raw[33, :] = [  0,   0, 230]
    pallete_raw[34, :] = [119,  11,  32]

    train2regular = [7, 8, 11, 12, 13, 17, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 31, 32, 33]

    for i in range(len(train2regular)):
        pallete[i, :] = pallete_raw[train2regular[i]+1, :]

    pallete = pallete.reshape(-1)

    return pallete

    this function is to get the colormap for visualizing the segmentation mask
    :param num_cls: the number of visulized class
    :return: the pallete
    
deeplab/demo.py