roboflow/supervision · error · ValueError

F1Score with `MetricTarget.MASKS` requires detections to inc

Error message

F1Score with `MetricTarget.MASKS` requires detections to include masks.

What it means

Error "F1Score with `MetricTarget.MASKS` requires detections to include masks." thrown in roboflow/supervision.

Source

Thrown at src/supervision/metrics/f1_score.py:535

        return result_f1_score

    def _detections_content(
        self, detections: Detections
    ) -> npt.NDArray[Any] | CompactMask:
        """Return boxes, masks or oriented bounding boxes from detections.

        For the mask target this may return a
        :class:`~supervision.detection.compact_mask.CompactMask` rather than a
        dense boolean array when the detections carry compact masks.
        """
        if self._metric_target == MetricTarget.BOXES:
            return cast(npt.NDArray[Any], detections.xyxy)
        if self._metric_target == MetricTarget.MASKS:
            if detections.mask is not None:
                # detections.mask is NDArray[bool] | CompactMask; return as-is.
                return detections.mask
            if len(detections) > 0:
                raise ValueError(
                    "F1Score with `MetricTarget.MASKS` requires detections to "
                    "include masks."
                )
            return self._make_empty_content()
        if self._metric_target == MetricTarget.ORIENTED_BOUNDING_BOXES:
            obb = detections.data.get(ORIENTED_BOX_COORDINATES)
            if obb is not None and len(obb) > 0:
                result_obb: npt.NDArray[np.float32] = np.array(obb, dtype=np.float32)
                return result_obb
            return self._make_empty_content()
        raise ValueError(f"Invalid metric target: {self._metric_target}")

    def _make_empty_content(self) -> npt.NDArray[Any]:
        if self._metric_target == MetricTarget.BOXES:
            empty_boxes: npt.NDArray[np.float32] = np.empty((0, 4), dtype=np.float32)
            return empty_boxes
        if self._metric_target == MetricTarget.MASKS:
            empty_masks: npt.NDArray[np.bool_] = np.empty((0, 0, 0), dtype=bool)

View on GitHub (pinned to 7f254d9784)

Solutions

1. Include masks in the Detections when using MetricTarget.MASKS with F1Score.
2. If masks are unavailable, use MetricTarget.BOXES instead.

When it happens

Trigger: Thrown at src/supervision/metrics/f1_score.py:535 when the library encounters an invalid state.

Common situations: See trigger scenarios.

AI-assisted analysis of roboflow/supervision@7f254d9784 (2026-08-15). Data as JSON: /api/errors/4a9a01359e084562. Report an issue: GitHub.