Function boundary_f1

src/depth_pro/eval/boundary_metrics.py:178–221

Calculate Boundary F1 score. Args: ---- pr (np.ndarray): Predicted depth matrix. gt (np.ndarray): Ground truth depth matrix. t (float): Threshold for comparison. return_p (bool, optional): If True, return precision. Defaults to False. return_r (bool,

(
    pr: np.ndarray,
    gt: np.ndarray,
    t: float,
    return_p: bool = False,
    return_r: bool = False,
)

def boundary_f1(
    pr: np.ndarray,
    gt: np.ndarray,
    t: float,
    return_p: bool = False,
    return_r: bool = False,
) -> float:
    """Calculate Boundary F1 score.

    Args:
    ----
        pr (np.ndarray): Predicted depth matrix.
        gt (np.ndarray): Ground truth depth matrix.
        t (float): Threshold for comparison.
        return_p (bool, optional): If True, return precision. Defaults to False.
        return_r (bool, optional): If True, return recall. Defaults to False.

    Returns:
    -------
        float: Boundary F1 score, or precision, or recall depending on the flags.

    """
    ap, bp, cp, dp = fgbg_depth(pr, t)
    ag, bg, cg, dg = fgbg_depth(gt, t)

    r = 0.25 * (
        np.count_nonzero(ap & ag) / max(np.count_nonzero(ag), 1)
        + np.count_nonzero(bp & bg) / max(np.count_nonzero(bg), 1)
        + np.count_nonzero(cp & cg) / max(np.count_nonzero(cg), 1)
        + np.count_nonzero(dp & dg) / max(np.count_nonzero(dg), 1)
    )
    p = 0.25 * (
        np.count_nonzero(ap & ag) / max(np.count_nonzero(ap), 1)
        + np.count_nonzero(bp & bg) / max(np.count_nonzero(bp), 1)
        + np.count_nonzero(cp & cg) / max(np.count_nonzero(cp), 1)
        + np.count_nonzero(dp & dg) / max(np.count_nonzero(dp), 1)
    )
    if r + p == 0:
        return 0.0
    if return_p:
        return p
    if return_r:
        return r
    return 2 * (r * p) / (r + p)


def get_thresholds_and_weights(