code: def __call__(self, data):
      imgs = data["image"]
  
      (
          img,
          gt_instance,
          training_mask,
          gt_kernel_instance,
          gt_kernel,
          gt_kernel_inner,
          training_mask_distance,
      ) = (
          imgs[0],
          imgs[1],
          imgs[2],
          imgs[3],
          imgs[4],
          imgs[5],
          imgs[6],
      )
  
      max_instance = np.max(gt_instance)  # num bbox
  
      # make centripetal shift
      gt_distance = np.zeros((2, *img.shape[0:2]), dtype=np.float32)
      for i in range(1, max_instance + 1):
          # kernel_reference
          ind = gt_kernel_inner == i
  
          if np.sum(ind) == 0:
              training_mask[gt_instance == i] = 0
              training_mask_distance[gt_instance == i] = 0
              continue
  
          kpoints = (
              np.array(np.where(ind))
              .transpose((1, 0))[:, ::-1]
              .astype("float32")
          )
  
          ind = (gt_instance == i) * (gt_kernel_instance == 0)
          if np.sum(ind) == 0:
              continue
          pixels = np.where(ind)
  
          points = (
              np.array(pixels)
              .transpose((1, 0))[:, ::-1]
              .astype("float32")
          )
  
          bbox_ind = self.jaccard(points, kpoints)
  
          offset_gt = kpoints[bbox_ind] - points
  
          gt_distance[:, pixels[0], pixels[1]] = offset_gt.T * 0.1
  
      img = Image.fromarray(img)
      img = img.convert("RGB")
  
      data["image"] = img
      data["gt_kernel"] = gt_kernel.astype("int64")
      data["training_mask"] = training_mask.astype("int64")
      data["gt_instance"] = gt_instance.astype("int64")
      data["gt_kernel_instance"] = gt_kernel_instance.astype("int64")
      data["training_mask_distance"] = training_mask_distance.astype(
          "int64"
      )
      data["gt_distance"] = gt_distance.astype("float32")
  
      return data
  
imports: import os
  import cv2
  import random
  import pyclipper
  import paddle
  import numpy
  from ppocr.utils.utility import check_install
  import scipy.io
  from PIL import Image
  import paddle.vision.transforms
label_desc: Use image node_id 3 for calling the MakeCentripetalShift obj's underlying member method code with example usage: obj.__call__(data) and returns: data