class_docstr: Calculate detection mean average precision.
  Currently support two types: 11point and integral
  
  Args:
      class_num (int): The class number.
      overlap_thresh (float): The threshold of overlap
          ratio between prediction bounding box and 
          ground truth bounding box for deciding 
          true/false positive. Default 0.5.
      map_type (str): Calculation method of mean average
          precision, currently support '11point' and
          'integral'. Default '11point'.
      is_bbox_normalized (bool): Whether bounding boxes
          is normalized to range[0, 1]. Default False.
      evaluate_difficult (bool): Whether to evaluate
          difficult bounding boxes. Default False.
      catid2name (dict): Mapping between category id and category name.
      classwise (bool): Whether per-category AP and draw
          P-R Curve or not.
class_docstr_tok: ["Calculate","detection","mean","average","precision",".","Currently","support","two","types",":","11point","and","integral","Args",":","class_num","(","int",")",":","The","class","number",".","overlap_thresh","(","float",")",":","The","threshold","of","overlap","ratio","between","prediction","bounding","box","and","ground","truth","bounding","box","for","deciding","true\/false","positive",".","Default","0.5.","map_type","(","str",")",":","Calculation","method","of","mean","average","precision",",","currently","support","'11point","'","and","'integral","'",".","Default","'11point","'",".","is_bbox_normalized","(","bool",")",":","Whether","bounding","boxes","is","normalized","to","range","[","0",",","1","]",".","Default","False",".","evaluate_difficult","(","bool",")",":","Whether","to","evaluate","difficult","bounding","boxes",".","Default","False",".","catid2name","(","dict",")",":","Mapping","between","category","id","and","category","name",".","classwise","(","bool",")",":","Whether","per-category","AP","and","draw","P-R","Curve","or","not","."]
docstr: Reset metric statics
docstr_tok: ["Reset","metric","statics"]
code: def reset(self):
      """
      Reset metric statics
      """
      self.class_score_poss = [[] for _ in range(self.class_num)]
      self.class_gt_counts = [0] * self.class_num
      self.mAP = 0.0
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import os
  import sys
  import numpy
  import itertools
  import paddle
  from ppdet.modeling.rbox_utils import poly2rbox_np
  from ppdet.utils.logger import setup_logger
label_desc: Use image node_id 3 for calling the DetectionMAP obj's underlying member method code with example usage: obj.reset() without return types