odifiedPanopticQuality(things = {0, 1}, stuffs = {6, 7})
            >>> metric.update(preds, target)
            >>> fig_, ax_ = metric.plot()

        .. plot::
            :scale: 75

            >>> # Example plotting multiple values
            >>> from torch import tensor
            >>> from torchmetrics.detection import ModifiedPanopticQuality
            >>> preds = tensor([[[[6, 0], [0, 0], [6, 0], [6, 0]],
            ...                  [[0, 0], [0, 0], [6, 0], [0, 1]],
            ...                  [[0, 0], [0, 0], [6, 0], [0, 1]],
            ...                  [[0, 0], [7, 0], [6, 0], [1, 0]],
            ...                  [[0, 0], [7, 0], [7, 0], [7, 0]]]])
            >>> target = tensor([[[[6, 0], [0, 1], [6, 0], [0, 1]],
            ...                   [[0, 1], [0, 1], [6, 0], [0, 1]],
            ...                   [[0, 1], [0, 1], [6, 0], [1, 0]],
            ...                   [[0, 1], [7, 0], [1, 0], [1, 0]],
            ...                   [[0, 1], [7, 0], [7, 0], [7, 0]]]])
            >>> metric = ModifiedPanopticQuality(things = {0, 1}, stuffs = {6, 7})
            >>> vals = []
            >>> for _ in range(20):
            ...     vals.append(metric(preds, target))
            >>> fig_, ax_ = metric.plot(vals)

        rJ