INNER CODE UNIT · Python

load_mask

castorini/daam · daam/evaluate.py:38

def load_mask(path: str) -> torch.Tensor:
    mask = np.array(Image.open(path))
    mask = torch.from_numpy(mask).float()[:, :, 3]  # use alpha channel
    mask = (mask > 0).float()

    return mask


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]

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