docstr: Initialize CocoEval using coco APIs for gt and dt.
  
  :param cocoGt: coco object with ground truth annotations
  :param cocoDt: coco object with detection results
  :return: None
docstr_tok: ["Initialize","CocoEval","using","coco","APIs","for","gt","and","dt",".",":","param","cocoGt",":","coco","object","with","ground","truth","annotations",":","param","cocoDt",":","coco","object","with","detection","results",":","return",":","None"]
code: def __init__(self, cocoGt=None, cocoDt=None, iouType="segm"):
      """Initialize CocoEval using coco APIs for gt and dt.
  
      :param cocoGt: coco object with ground truth annotations
      :param cocoDt: coco object with detection results
      :return: None
      """
      if not iouType:
          print("iouType not specified. use default iouType segm")
      self.cocoGt = cocoGt  # ground truth COCO API
      self.cocoDt = cocoDt  # detections COCO API
      self.params = {}  # evaluation parameters
      self.evalVids = defaultdict(
          list
      )  # per-image per-category evaluation results [KxAxI] elements
      self.eval = {}  # accumulated evaluation results
      self._gts = defaultdict(list)  # gt for evaluation
      self._dts = defaultdict(list)  # dt for evaluation
      self.params = Params(iouType=iouType)  # parameters
      self._paramsEval = {}  # parameters for evaluation
      self.stats = []  # result summarization
      self.ious = {}  # ious between all gts and dts
      if cocoGt is not None:
          self.params.vidIds = sorted(cocoGt.getVidIds())
          self.params.catIds = sorted(cocoGt.getCatIds())
  
imports: import copy
  import datetime
  import time
  from collections import defaultdict
  import numpy
  from pycocotools import mask
label_desc: Use image node_id 1 to create a new YTVISeval object  with example: obj = YTVISeval(cocoGt, cocoDt, iouType)