INNER CODE UNIT · Python

compute_ioa

castorini/daam · daam/evaluate.py:26

def compute_ioa(a: torch.Tensor, b: torch.Tensor) -> float:
    if a.shape[0] != b.shape[0]:
        a = F.interpolate(a.unsqueeze(0).unsqueeze(0).float(), size=b.shape, mode='bicubic').squeeze()
        a[a < 1] = 0
        a[a >= 1] = 1

    intersection = (a * b).sum()
    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

View source record →