parameters: (self, cocoGt=None, cocoDt=None)
docstring: 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
docstring_summary: 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
docstring_tokens: 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
function: def __init__(self, cocoGt=None, cocoDt=None):
          '''
          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
          '''
          self.cocoGt   = cocoGt              # ground truth COCO API
          self.cocoDt   = cocoDt              # detections COCO API
          self.params   = {}                  # evaluation parameters
          self.evalImgs = 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()              # parameters
          self._paramsEval = {}               # parameters for evaluation
          self.stats = []                     # result summarization
          self.ious = {}                      # ious between all gts and dts
          if not cocoGt is None:
              self.params.imgIds = sorted(cocoGt.getImgIds())
              self.params.catIds = sorted(cocoGt.getCatIds())
function_tokens: def __init__ ( self , cocoGt = None , cocoDt = None ) : self . cocoGt = cocoGt # ground truth COCO API self . cocoDt = cocoDt # detections COCO API self . params = { } # evaluation parameters self . evalImgs = 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 ( ) # parameters self . _paramsEval = { } # parameters for evaluation self . stats = [ ] # result summarization self . ious = { } # ious between all gts and dts if not cocoGt is None : self . params . imgIds = sorted ( cocoGt . getImgIds ( ) ) self . params . catIds = sorted ( cocoGt . getCatIds ( ) )