code: def mask_pic(img, mask):
      mask_mat = mask
      mask_mat = mask_mat.astype(np.float32)
      mask_mat = cv2.GaussianBlur(mask_mat, (0, 0), 1)
      mask_mat = mask_mat / np.max(mask_mat)
      mask_mat = mask_mat * 255
      mask_mat[mask_mat < 255] = 0
      mask_mat = mask_mat.astype(np.uint8)
      mask_mat = cv2.GaussianBlur(mask_mat, (0, 0), 3)
      mask_mat = get_gray_map(mask_mat)
      mask_mat = normalize_pic(mask_mat)
      mask_mat = resize_img_512(mask_mat)
      super_from = np.multiply(img, mask_mat)
      return super_from
  
imports: import numpy
  import cv2
  from scipy import ndimage
label_desc: Use image node_id 10 for calling a global function with example usage: mask_pic(img, mask) and returns: super_from