INNER CODE UNIT · Python

area

castorini/daam · daam/evaluate.py:33

    area = a.sum()

    return (intersection / (area + 1e-8)).item()


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

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