def generate_results(
        self,
        samples,
        matches,
        eval_key=None,
        classes=None,
        missing=None,
        progress=None,
    ):
        """Generates aggregate evaluation results for the samples.

        If ``self.config.compute_mAP`` is True, this method performs COCO-style
        evaluation as in :meth:`evaluate` to generate precision and recall
        sweeps over the range of IoU thresholds in ``self.config.iou_threshs``.
        In this case, a :class:`COCODetectionResults` instance is returned that
        can compute mAP and PR curves.

        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
            progress (None): whether to render a progress bar (True/False), use
                the default value ``fiftyone.config.show_progress_bars``
                (None), or a progress callback function to invoke instead

        Returns:
            a :class:`DetectionResults`
        """
        if not self.config.compute_mAP:
            return DetectionResults(
                samples,
                self.config,
                eval_key,
                matches,
                classes=classes,
                missing=missing,
                backend=self,
            )

        (
            precision,
            recall,
            thresholds,
            iou_threshs,
            classes,
            recall_sweep,
        ) = _compute_pr_curves(
            samples, self.config, classes=classes, progress=progress
        )

        return COCODetectionResults(
            samples,
            self.config,
            eval_key,
            matches,
            precision,
            recall,
            iou_threshs,
            classes,
            recall_sweep=recall_sweep,
            thresholds=thresholds,
            missing=missing,
            backend=self,
        )
Generates aggregate evaluation results for the samples.

        If ``self.config.compute_mAP`` is True, this method performs COCO-style
        evaluation as in :meth:`evaluate` to generate precision and recall
        sweeps over the range of IoU thresholds in ``self.config.iou_threshs``.
        In this case, a :class:`COCODetectionResults` instance is returned that
        can compute mAP and PR curves.

        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
            progress (None): whether to render a progress bar (True/False), use
                the default value ``fiftyone.config.show_progress_bars``
                (None), or a progress callback function to invoke instead

        Returns:
            a :class:`DetectionResults`
        
fiftyone/utils/eval/coco.py