code: def success_overlap(gt_bb, result_bb, n_frame):
      """get success_overlap score
  
      Parameters
      ----------
          result_bb : nd.array
              2d array of N x [x,y,w,h]
          n_frame : int
              frame number
  
      Return
      ----------
          success score
      """
      thresholds_overlap = np.arange(0, 1.05, 0.05)
      success = np.zeros(len(thresholds_overlap))
      iou = np.ones(len(gt_bb)) * (-1)
      mask = np.sum(gt_bb[:, 2:] > 0, axis=1) == 2
      iou[mask] = overlap_ratio(gt_bb[mask], result_bb[mask])
      for i, per_threshold in enumerate(thresholds_overlap):
          success[i] = np.sum(iou > 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 3 for calling a global function with example usage: success_overlap(gt_bb, result_bb, n_frame) and returns: success