def evaluate_segmentations(
        self,
        pred_field,
        gt_field="ground_truth",
        eval_key=None,
        mask_targets=None,
        method=None,
        progress=None,
        **kwargs,
    ):
        """Evaluates the specified semantic segmentation masks in this
        collection with respect to the specified ground truth masks.

        If the size of a predicted mask does not match the ground truth mask,
        it is resized to match the ground truth.

        By default, this method simply performs pixelwise evaluation of the
        full masks, but other strategies such as boundary-only evaluation can
        be configured by passing additional parameters for the method's
        config class as ``kwargs``.

        The natively provided ``method`` values and their associated configs
        are:

        -   ``"simple"``: :class:`fiftyone.utils.eval.segmentation.SimpleEvaluationConfig`

        If an ``eval_key`` is provided, the accuracy, precision, and recall of
        each sample is recorded in top-level fields of each sample::

             Accuracy: sample.<eval_key>_accuracy
            Precision: sample.<eval_key>_precision
               Recall: sample.<eval_key>_recall

        In addition, when evaluating frame-level masks, the accuracy,
        precision, and recall of each frame if recorded in the following
        frame-level fields::

             Accuracy: frame.<eval_key>_accuracy
            Precision: frame.<eval_key>_precision
               Recall: frame.<eval_key>_recall

        .. note::

            The mask values ``0`` and ``#000000`` are treated as a background
            class for the purposes of computing evaluation metrics like
            precision and recall.

        Args:
            pred_field: the name of the field containing the predicted
                :class:`fiftyone.core.labels.Segmentation` instances
            gt_field ("ground_truth"): the name of the field containing the
                ground truth :class:`fiftyone.core.labels.Segmentation`
                instances
            eval_key (None): a string key to use to refer to this evaluation
            mask_targets (None): a dict mapping pixel values or RGB hex strings
                to labels. If not provided, the observed values are used as
                labels
            method (None): a string specifying the evaluation method to use.
                The supported values are
                ``fo.evaluation_config.segmentation_backends.keys()`` and the
                default is ``fo.evaluation_config.segmentation_default_backend``
            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
            **kwargs: optional keyword arguments for the constructor of the
                :class:`fiftyone.utils.eval.segmentation.SegmentationEvaluationConfig`
                being used

        Returns:
            a :class:`fiftyone.utils.eval.segmentation.SegmentationResults`
        """
        return foue.evaluate_segmentations(
            self,
            pred_field,
            gt_field=gt_field,
            eval_key=eval_key,
            mask_targets=mask_targets,
            method=method,
            progress=progress,
            **kwargs,
        )
Evaluates the specified semantic segmentation masks in this
        collection with respect to the specified ground truth masks.

        If the size of a predicted mask does not match the ground truth mask,
        it is resized to match the ground truth.

        By default, this method simply performs pixelwise evaluation of the
        full masks, but other strategies such as boundary-only evaluation can
        be configured by passing additional parameters for the method's
        config class as ``kwargs``.

        The natively provided ``method`` values and their associated configs
        are:

        -   ``"simple"``: :class:`fiftyone.utils.eval.segmentation.SimpleEvaluationConfig`

        If an ``eval_key`` is provided, the accuracy, precision, and recall of
        each sample is recorded in top-level fields of each sample::

             Accuracy: sample.<eval_key>_accuracy
            Precision: sample.<eval_key>_precision
               Recall: sample.<eval_key>_recall

        In addition, when evaluating frame-level masks, the accuracy,
        precision, and recall of each frame if recorded in the following
        frame-level fields::

             Accuracy: frame.<eval_key>_accuracy
            Precision: frame.<eval_key>_precision
               Recall: frame.<eval_key>_recall

        .. note::

            The mask values ``0`` and ``#000000`` are treated as a background
            class for the purposes of computing evaluation metrics like
            precision and recall.

        Args:
            pred_field: the name of the field containing the predicted
                :class:`fiftyone.core.labels.Segmentation` instances
            gt_field ("ground_truth"): the name of the field containing the
                ground truth :class:`fiftyone.core.labels.Segmentation`
                instances
            eval_key (None): a string key to use to refer to this evaluation
            mask_targets (None): a dict mapping pixel values or RGB hex strings
                to labels. If not provided, the observed values are used as
                labels
            method (None): a string specifying the evaluation method to use.
                The supported values are
                ``fo.evaluation_config.segmentation_backends.keys()`` and the
                default is ``fo.evaluation_config.segmentation_default_backend``
            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
            **kwargs: optional keyword arguments for the constructor of the
                :class:`fiftyone.utils.eval.segmentation.SegmentationEvaluationConfig`
                being used

        Returns:
            a :class:`fiftyone.utils.eval.segmentation.SegmentationResults`
        
fiftyone/core/collections.py