def mAR(self, classes=None):
        """Computes COCO-style mean average recall (mAR) for the specified
        classes.

        See `this page <https://github.com/cocodataset/cocoapi/blob/master/PythonAPI/pycocotools/cocoeval.py>`_
        for more details about COCO-style mAR.

        Args:
            classes (None): a list of classes for which to compute mAR

        Returns:
            the mAR in ``[0, 1]``
        """
        if self._classwise_AR is None:
            raise Exception(
                "Classwise AR is not available. mAR can't be computed."
            )

        if classes is not None:
            class_inds = np.array([self._get_class_index(c) for c in classes])
            classwise_AR = self._classwise_AR[class_inds]
        else:
            classwise_AR = self._classwise_AR

        classwise_AR = classwise_AR[classwise_AR > -1]
        if classwise_AR.size == 0:
            return -1

        return np.mean(classwise_AR)
Computes COCO-style mean average recall (mAR) for the specified
        classes.

        See `this page <https://github.com/cocodataset/cocoapi/blob/master/PythonAPI/pycocotools/cocoeval.py>`_
        for more details about COCO-style mAR.

        Args:
            classes (None): a list of classes for which to compute mAR

        Returns:
            the mAR in ``[0, 1]``
        
fiftyone/utils/eval/coco.py