code: def stats_confusion(confusion):
      """confusion matrix to TP, FP, TN, FN"""
      FP = confusion.sum(axis=0) - np.diag(confusion)
      FN = confusion.sum(axis=1) - np.diag(confusion)
      TP = np.diag(confusion)
      TN = confusion.sum() - (TP + FN + TP)
      return TN, FP, FN, TP
  
imports: import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: stats_confusion(confusion) and returns: TN,  FP,  FN,  TP