src.evaluation_metric.matching_recall¶
- src.evaluation_metric.matching_recall(pmat_pred: torch.Tensor, pmat_gt: torch.Tensor, ns: torch.Tensor) torch.Tensor [source]¶
Matching Recall between predicted permutation matrix and ground truth permutation matrix.
\[\text{matching recall} = \frac{tr(\mathbf{X}\cdot {\mathbf{X}^{gt}}^\top)}{\sum \mathbf{X}^{gt}}\]- Parameters
pmat_pred – \((b\times n_1 \times n_2)\) predicted permutation matrix \((\mathbf{X})\)
pmat_gt – \((b\times n_1 \times n_2)\) ground truth permutation matrix \((\mathbf{X}^{gt})\)
ns – \((b)\) number of exact pairs. We support batched instances with different number of nodes, and
ns
is required to specify the exact number of nodes of each instance in the batch.
- Returns
\((b)\) matching recall
Note
This function is equivalent to “matching accuracy” if the matching problem has no outliers.