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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code: def _from_dict(cls, d, samples, config, eval_key, **kwargs):
      precision = d["precision"]
      recall = d["recall"]
      thresholds = d.get("thresholds", None)
      return super()._from_dict(
          d,
          samples,
          config,
          eval_key,
          precision=precision,
          recall=recall,
          thresholds=thresholds,
          **kwargs,
      )
  
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 5 for calling the OpenImagesDetectionResults obj's underlying member method code with example usage: obj._from_dict(cls, d, samples, config, eval_key) and returns: super