roboflow/supervision · error · ValueError

Precision metric requires `confidence` on predictions.

Error message

Precision metric requires `confidence` on predictions.

What it means

Error "Precision metric requires `confidence` on predictions." thrown in roboflow/supervision.

Source

Thrown at src/supervision/metrics/precision.py:239

                if len(predictions) == 0:
                    target_class_ids = np.asarray(targets.class_id, dtype=np.int32)[
                        target_size_mask
                    ]
                    if len(target_class_ids) == 0:
                        continue
                    stats.append(
                        (
                            np.zeros((0, iou_thresholds.size), dtype=bool),
                            np.zeros((0, iou_thresholds.size), dtype=bool),
                            np.zeros((0,), dtype=np.float32),
                            np.zeros((0,), dtype=int),
                            target_class_ids,
                        )
                    )

                else:
                    if predictions.confidence is None:
                        raise ValueError(
                            "Precision metric requires `confidence` on predictions."
                        )
                    prediction_class_ids = np.asarray(
                        predictions.class_id, dtype=np.int32
                    )
                    target_class_ids = np.asarray(targets.class_id, dtype=np.int32)
                    prediction_confidence = np.asarray(
                        predictions.confidence, dtype=np.float32
                    )
                    if self._metric_target == MetricTarget.BOXES:
                        iou = box_iou_batch(target_contents, prediction_contents)
                    elif self._metric_target == MetricTarget.MASKS:
                        iou = mask_iou_batch(target_contents, prediction_contents)
                    elif self._metric_target == MetricTarget.ORIENTED_BOUNDING_BOXES:
                        iou = oriented_box_iou_batch(
                            target_contents, prediction_contents
                        )
                    else:

View on GitHub (pinned to 7f254d9784)

Solutions

1. Set confidence on the prediction Detections before computing Precision.
2. If scores are unavailable, supply a placeholder confidence array.

When it happens

Trigger: Thrown at src/supervision/metrics/precision.py:239 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/c6e015d866888a0b. Report an issue: GitHub.