INNER CODE UNIT · Python

UnsupervisedEvaluator

castorini/daam · daam/evaluate.py:46

class UnsupervisedEvaluator:
    def __init__(self, name: str = 'UnsupervisedEvaluator'):
        self.name = name
        self.ious = defaultdict(list)
        self.num_samples = 0

    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))

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