code: def eval_metric(labels, scores, metric="roc"):
      if metric == "pro":
          return pro(labels, scores)
      if metric == "roc":
          return roc(labels, scores)
      else:
          raise NotImplementedError("Check the evaluation metric.")
  
imports: import os
  import argparse
  import numpy
  import matplotlib
  import matplotlib.pyplot
  from sklearn.metrics import roc_curve, auc
  from tqdm import tqdm
  from skimage import measure, morphology
  from skimage.segmentation import mark_boundaries
  import paddle
label_desc: Use image node_id 19 for calling a global function with example usage: eval_metric(labels, scores, metric) and returns: pro, roc