Display images on the command line using 4 shades of gray

display_img.py

import numpy as np

__author__ = 'Tim Gianitsos'

def display_img(img):
    '''
    img: a 2D array of ints
    '''
    dark_black = '\u001B[40m  '
    light_black = '\u001B[100m  '
    dark_white = '\u001B[47m  '
    light_white = '\u001B[107m  '
    reset_color = '\u001B[0m'
    percs = np.percentile(np.unique(img), (25, 50, 75))
    for r in range(img.shape[0]):
        for c in range(img.shape[1]):
            print(
                dark_black if img[r, c] <= percs[0] else
                light_black if img[r, c] <= percs[1] else
                dark_white if img[r, c] <= percs[2] else light_white,
                end=""
            )
        print(reset_color)
    print()

if __name__ == '__main__':
    try:
        from sklearn import datasets
        batch_size = 10
        imgs = datasets.load_digits().data[:batch_size].reshape(
            batch_size, 8, 8
        )
    except ModuleNotFoundError:
        imgs = np.array([[
            [0.,  0., 11., 12.,  0.,  0.,  0.,  0.,],
            [0.,  2., 16., 16., 16., 13.,  0.,  0.,],
            [0.,  3., 16., 12., 10., 14.,  0.,  0.,],
            [0.,  1., 16.,  1., 12., 15.,  0.,  0.,],
            [0.,  0., 13., 16.,  9., 15.,  2.,  0.,],
            [0.,  0.,  0.,  3.,  0.,  9., 11.,  0.,],
            [0.,  0.,  0.,  0.,  9., 15.,  4.,  0.,],
            [0.,  0.,  9., 12., 13.,  3.,  0.,  0.,],
        ]])
    for img in imgs:
        display_img(img)