def _mask_border_keypoints(image, keypoints, dist):
    """Removes keypoints that are within dist pixels from the image border."""
    width = image.shape[0]
    height = image.shape[1]

    keypoints_filtering_mask = ((dist - 1 < keypoints[:, 0]) &
                                (keypoints[:, 0] < width - dist + 1) &
                                (dist - 1 < keypoints[:, 1]) &
                                (keypoints[:, 1] < height - dist + 1))

    return keypoints_filtering_mask


def pairwise_hamming_distance(array1, array2):
    """**Experimental function**.

    Calculate hamming dissimilarity measure between two sets of
    vectors.

    Parameters
    ----------
    array1 : (P1, D) array
        P1 vectors of size D.
    array2 : (P2, D) array
        P2 vectors of size D.

    Returns
    -------
    distance : (P1, P2) array of dtype float
        2D ndarray with value at an index (i, j) representing the hamming
        distance in the range [0, 1] between ith vector in array1 and jth
        vector in array2.

    """
    distance = (array1[:, None] != array2[None]).mean(axis=2)
    return distance