class_docstr: Base class for detection evaluation methods.
  
  Args:
      config: a :class:`DetectionEvaluationConfig`
class_docstr_tok: ["Base","class","for","detection","evaluation","methods",".","Args",":","config",":","a",":","class",":","`","DetectionEvaluationConfig","`"]
docstr: Generates aggregate evaluation results for the samples.
  
  Subclasses may perform additional computations here such as IoU sweeps
  in order to generate mAP, PR curves, etc.
  
  Args:
      samples: a :class:`fiftyone.core.collections.SampleCollection`
      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
      eval_key (None): the evaluation key for this evaluation
      classes (None): the list of possible classes. If not provided, the
          observed ground truth/predicted labels are used for results
          purposes
      missing (None): a missing label string. Any unmatched objects are
          given this label for results purposes
  
  Returns:
      a :class:`DetectionResults`
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code: def generate_results(
      self, samples, matches, eval_key=None, classes=None, missing=None
  ):
      """Generates aggregate evaluation results for the samples.
  
      Subclasses may perform additional computations here such as IoU sweeps
      in order to generate mAP, PR curves, etc.
  
      Args:
          samples: a :class:`fiftyone.core.collections.SampleCollection`
          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
          eval_key (None): the evaluation key for this evaluation
          classes (None): the list of possible classes. If not provided, the
              observed ground truth/predicted labels are used for results
              purposes
          missing (None): a missing label string. Any unmatched objects are
              given this label for results purposes
  
      Returns:
          a :class:`DetectionResults`
      """
      return DetectionResults(
          samples,
          self.config,
          eval_key,
          matches,
          classes=classes,
          missing=missing,
          backend=self,
      )
  
imports: from copy import deepcopy
  import inspect
  import itertools
  import logging
  import numpy
  import eta.core.utils
  import fiftyone
  import fiftyone.core.evaluation
  import fiftyone.core.fields
  import fiftyone.core.labels
  import fiftyone.core.utils
  import fiftyone.core.validation
  from .base import BaseEvaluationResults
label_desc: Use image node_id 4 for calling the DetectionEvaluation obj's underlying member method code with example usage: obj.generate_results(samples, matches, eval_key, classes, missing) and returns: DetectionResults