code: def mean_precision(self, out_16_13=False):
      Precision = np.diag(
          self.confusion_matrix
      ) / self.confusion_matrix.sum(axis=0)
      if self.synthia:
          Precision_16 = np.nanmean(Precision[: self.ignore_index])
          Precision_13 = np.nanmean(Precision[synthia_set_16_to_13])
          return Precision_16, Precision_13
      if out_16_13:
          Precision_16 = np.nanmean(Precision[synthia_set_16])
          Precision_13 = np.nanmean(Precision[synthia_set_13])
          return Precision_16, Precision_13
      Precision = np.nanmean(Precision[: self.ignore_index])
      return Precision
  
imports: import os
  import time
  import tqdm
  import numpy
  from PIL import Image
  import paddle
  import paddle.nn.functional
  from paddleseg.utils import metrics, TimeAverager, calculate_eta, logger, progbar
  import datasets
  from utils import save_imgs
label_desc: Use image node_id 6 for calling the Eval obj's underlying member method code with example usage: obj.mean_precision(out_16_13) and returns: Precision, Precision_16,  Precision_13, Precision_16,  Precision_13