class_docstr: Class that stores the results of an Open Images detection evaluation.
  
  Args:
      samples: the :class:`fiftyone.core.collections.SampleCollection` used
      config: the :class:`OpenImagesEvaluationConfig` used
      eval_key: the evaluation key
      matches: a list of
          ``(gt_label, pred_label, iou, pred_confidence, gt_id, pred_id)``
          matches. Either label can be ``None`` to indicate an unmatched
          object
      precision: a dict of per-class precision values
      recall: a dict of per-class recall values
      classes: the list of possible classes
      thresholds (None): an optional dict of per-class decision thresholds
      missing (None): a missing label string. Any unmatched objects are
          given this label for evaluation purposes
      backend (None): a :class:`OpenImagesEvaluation` backend
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docstr: Computes Open Images-style mean average precision (mAP) for the
  specified classes.
  
  See `this page <https://storage.googleapis.com/openimages/web/evaluation.html>`_
  for more details about Open Images-style mAP.
  
  Args:
      classes (None): a list of classes for which to compute mAP
  
  Returns:
      the mAP in ``[0, 1]``
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code: def mAP(self, classes=None):
      """Computes Open Images-style mean average precision (mAP) for the
      specified classes.
  
      See `this page <https://storage.googleapis.com/openimages/web/evaluation.html>`_
      for more details about Open Images-style mAP.
  
      Args:
          classes (None): a list of classes for which to compute mAP
  
      Returns:
          the mAP in ``[0, 1]``
      """
      if classes is not None:
          self._validate_classes(classes)
          classwise_AP = [self._classwise_AP[c] for c in classes]
      else:
          classwise_AP = list(self._classwise_AP.values())
  
      classwise_AP = np.array(classwise_AP)
      classwise_AP = classwise_AP[classwise_AP > -1]
      if classwise_AP.size == 0:
          return -1
  
      return np.mean(classwise_AP)
  
imports: from collections import defaultdict
  from copy import deepcopy
  import numpy
  import fiftyone.core.plots
  import fiftyone.utils.iou
  from .detection import DetectionEvaluation, DetectionEvaluationConfig, DetectionResults
label_desc: Use image node_id 3 for calling the OpenImagesDetectionResults obj's underlying member method code with example usage: obj.mAP(classes) and returns: np, unknown