code: def tia_stretch(src, segment=4):
      img_h, img_w = src.shape[:2]
  
      cut = img_w // segment
      thresh = cut * 4 // 5
  
      src_pts = list()
      dst_pts = list()
  
      src_pts.append([0, 0])
      src_pts.append([img_w, 0])
      src_pts.append([img_w, img_h])
      src_pts.append([0, img_h])
  
      dst_pts.append([0, 0])
      dst_pts.append([img_w, 0])
      dst_pts.append([img_w, img_h])
      dst_pts.append([0, img_h])
  
      half_thresh = thresh * 0.5
  
      for cut_idx in np.arange(1, segment, 1):
          move = np.random.randint(thresh) - half_thresh
          src_pts.append([cut * cut_idx, 0])
          src_pts.append([cut * cut_idx, img_h])
          dst_pts.append([cut * cut_idx + move, 0])
          dst_pts.append([cut * cut_idx + move, img_h])
  
      trans = WarpMLS(src, src_pts, dst_pts, img_w, img_h)
      dst = trans.generate()
  
      return dst
  
imports: import numpy
  from .warp_mls import WarpMLS
label_desc: Use image node_id 2 for calling a global function with example usage: tia_stretch(src, segment) and returns: dst