docs: def best_diff(img1, img2, opts):
      """Find the best alignment of two images that minimizes the differences.
  
      Returns (diff, alignments) where ``diff`` is a difference map, and
      ``alignments`` is a tuple ((x1, y2), (x2, y2)).
  
      See ``diff()`` for the description of the alignment numbers.
      """
      w1, h1 = img1.size
      w2, h2 = img2.size
      w, h = min(w1, w2), min(h1, h2)
      best = None
      best_value = 255 * w * h + 1
  
      xr = abs(w1 - w2) + 1
      yr = abs(h1 - h2) + 1
  
      p = Progress(xr * yr, timeout=opts.timeout)
      for x in range(xr):
          if w1 > w2:
              x1, x2 = x, 0
          else:
              x1, x2 = 0, x
          for y in range(yr):
              if h1 > h2:
                  y1, y2 = y, 0
              else:
                  y1, y2 = 0, y
              p.next()
              this = diff(img1, img2, (x1, y1), (x2, y2))
              this_value = diff_badness(this)
              if this_value < best_value:
                  best = this
                  best_value = this_value
                  best_pos = (x1, y1), (x2, y2)
      return best, best_pos