code: def fwiou(self, out_16_13=False):
      FWIoU = np.multiply(
          np.sum(self.confusion_matrix, axis=1),
          np.diag(self.confusion_matrix),
      )
      FWIoU = FWIoU / (
          np.sum(self.confusion_matrix, axis=1)
          + np.sum(self.confusion_matrix, axis=0)
          - np.diag(self.confusion_matrix)
      )
      if self.synthia:
          FWIoU_16 = np.sum(
              i for i in FWIoU if not np.isnan(i)
          ) / np.sum(self.confusion_matrix)
          FWIoU_13 = np.sum(
              i for i in FWIoU[synthia_set_16_to_13] if not np.isnan(i)
          ) / np.sum(self.confusion_matrix)
          return FWIoU_16, FWIoU_13
      if out_16_13:
          FWIoU_16 = np.sum(
              i for i in FWIoU[synthia_set_16] if not np.isnan(i)
          ) / np.sum(self.confusion_matrix)
          FWIoU_13 = np.sum(
              i for i in FWIoU[synthia_set_13] if not np.isnan(i)
          ) / np.sum(self.confusion_matrix)
          return FWIoU_16, FWIoU_13
      FWIoU = np.sum(i for i in FWIoU if not np.isnan(i)) / np.sum(
          self.confusion_matrix
      )
  
      return FWIoU
  
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 5 for calling the Eval obj's underlying member method code with example usage: obj.fwiou(out_16_13) and returns: FWIoU, FWIoU_16,  FWIoU_13, FWIoU_16,  FWIoU_13