code: def edge_pixels_from_mask(mask):
      
  
      edge_pixel_total = total_edge_pixels_from_mask(mask)
  
      edge_pixels = np.zeros(edge_pixel_total)
      edge_index = 0
      regular_index = 0
  
      for y in range(mask.shape[0]):
          for x in range(mask.shape[1]):
              if not mask[y, x]:
                  if mask[y + 1, x] or mask[y - 1, x] or mask[y, x + 1] or mask[y, x - 1] or \
                          mask[y + 1, x + 1] or mask[y + 1, x - 1] or mask[y - 1, x + 1] or mask[y - 1, x - 1]:
                      edge_pixels[edge_index] = regular_index
                      edge_index += 1
  
                  regular_index += 1
  
      return edge_pixels
docs: Compute a 1D array listing all edge pixel indexes in the masks. An edge pixel is a pixel which is not fully \
      surrounding by False masks values i.e. it is on an edge.