code: def _fast_hist(self, label_true, label_pred, n_class):
      mask = (label_true >= 0) & (label_true < n_class)
  
      if np.sum((label_pred[mask] < 0)) > 0:
          print(label_pred[label_pred < 0])
      hist = np.bincount(
          n_class * label_true[mask].astype(int) + label_pred[mask],
          minlength=n_class**2,
      ).reshape(n_class, n_class)
      return hist
  
file_path: PaddleOCR/benchmark/PaddleOCR_DBNet/utils/metrics.py
imports: import numpy
label_desc: Use image node_id 2 for calling the runningScore obj's underlying member method code with example usage: obj._fast_hist(label_true, label_pred, n_class) and returns: hist