class_docstr: SiamRPN OPEBenchmark have eval_success, precision to select.
  eval_success is  distance between the center point of the predicted position
  precision is Compute overlap ratio between two rects through thresholds_overlap
  Parameters
  ----------
      dataset
          dataset Benchmark
class_docstr_tok: ["SiamRPN","OPEBenchmark","have","eval_success",",","precision","to","select",".","eval_success","is","distance","between","the","center","point","of","the","predicted","position","precision","is","Compute","overlap","ratio","between","two","rects","through","thresholds_overlap","Parameters","--","--","--","--","--","dataset","dataset","Benchmark"]
code: def __init__(self, dataset):
      self.dataset = dataset
  
file_path: gluon-cv/gluoncv/utils/metrics/tracking.py
imports: import numpy
  from ..filesystem import try_import_colorama
label_desc: Use image node_id 1 to create a new OPEBenchmark object  with example: obj = OPEBenchmark(dataset)