code: def success_error(gt_center, result_center, thresholds, n_frame):
      """get success_error score
  
      Parameters
      ----------
          gt_center : np.ndarray
              2d array of N x [x,y,w,h]
          result_center : np.ndarray
              2d array of N x [x,y,w,h]
          thresholds : float
              error float
          n_frame : int
              frame number
  
      Return
      ----------
          success_error score
      """
      success = np.zeros(len(thresholds))
      dist = np.ones(len(gt_center)) * (-1)
      mask = np.sum(gt_center > 0, axis=1) == 2
      dist[mask] = np.sqrt(
          np.sum(
              np.power(gt_center[mask] - result_center[mask], 2), axis=1
          )
      )
      for i, per_threshold in enumerate(thresholds):
          success[i] = np.sum(dist <= per_threshold) / float(n_frame)
      return success
  
file_path: gluon-cv/gluoncv/utils/metrics/tracking.py
imports: import numpy
  from ..filesystem import try_import_colorama
label_desc: Use image node_id 4 for calling a global function with example usage: success_error(gt_center, result_center, thresholds, n_frame) and returns: success