INNER CODE UNIT · Python

log_iou

castorini/daam · daam/evaluate.py:52

    def log_iou(self, preds: Union[torch.Tensor, List[torch.Tensor]], truth: torch.Tensor, gt_idx: int = 0, pred_idx: int = 0):
        if not isinstance(preds, list):
            preds = [preds]

        iou = max(compute_iou(pred, truth) for pred in preds)
        self.ious[gt_idx].append((pred_idx, iou))

    @property
    def mean_iou(self) -> float:
        n = max(max(self.ious), max([y[0] for x in self.ious.values() for y in x])) + 1
        iou_matrix = np.zeros((n, n))
        count_matrix = np.zeros((n, n))

        for gt_idx, ious in self.ious.items():
            for pred_idx, iou in ious:
                iou_matrix[gt_idx, pred_idx] += iou
                count_matrix[gt_idx, pred_idx] += 1

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