spam

loss = [[1,0,1,1],
        [1,0,1,1],
        [1,1,1,0],
        [1,1,1,1]]
import numpy as np
from scipy.misc import imsave
im = np.array(loss).astype(float)
gap_width = 4
while im.shape[0] < 1024*4:
  new_im = np.zeros([gap_width*4,gap_width*4])
  new_im[:gap_width,:gap_width] = im
  new_im[:gap_width,2*gap_width:3*gap_width] = im
  new_im[:gap_width,3*gap_width:] = im
  
  new_im[gap_width:2*gap_width,:] = new_im[:gap_width,:]

  new_im[2*gap_width:,:2*gap_width] = new_im[:2*gap_width,2*gap_width:]

  new_im[2*gap_width:,2*gap_width:] = new_im[:2*gap_width,2*gap_width:]
  new_im[2*gap_width:3*gap_width,3*gap_width:] = 0
  im = new_im
  gap_width *= 4
imsave("test.png",im*255)