docstr: Returns accuracy score evaluation result.
  - overall accuracy
  - mean accuracy
  - mean IU
  - fwavacc
docstr_tok: ["Returns","accuracy","score","evaluation","result",".","-","overall","accuracy","-","mean","accuracy","-","mean","IU","-","fwavacc"]
code: def get_scores(self):
      """Returns accuracy score evaluation result.
      - overall accuracy
      - mean accuracy
      - mean IU
      - fwavacc
      """
      hist = self.confusion_matrix
      acc = np.diag(hist).sum() / (hist.sum() + 0.0001)
      acc_cls = np.diag(hist) / (hist.sum(axis=1) + 0.0001)
      acc_cls = np.nanmean(acc_cls)
      iu = np.diag(hist) / (
          hist.sum(axis=1) + hist.sum(axis=0) - np.diag(hist) + 0.0001
      )
      mean_iu = np.nanmean(iu)
      freq = hist.sum(axis=1) / (hist.sum() + 0.0001)
      fwavacc = (freq[freq > 0] * iu[freq > 0]).sum()
      cls_iu = dict(zip(range(self.n_classes), iu))
  
      return {
          "Overall Acc": acc,
          "Mean Acc": acc_cls,
          "FreqW Acc": fwavacc,
          "Mean IoU": mean_iu,
      }, cls_iu
  
file_path: PaddleOCR/benchmark/PaddleOCR_DBNet/utils/metrics.py
imports: import numpy
label_desc: Use image node_id 4 for calling the runningScore obj's underlying member method code with example usage: obj.get_scores() and returns: dict,  cls_iu