general_metrics.py 文件源码

def get_score(self, algo_result, gt, scene, with_visualization=False):
        diffs = np.abs(algo_result - gt) * self.factor
        mask = self.get_evaluation_mask(scene) * misc.get_mask_valid(diffs) * misc.get_mask_valid(algo_result)
        sorted_diffs = np.sort(diffs[mask])
        idx = np.size(sorted_diffs) * self.percentage / 100.
        score = sorted_diffs[int(idx)]

        if not with_visualization:
            return score

        with np.errstate(invalid="ignore"):
            m_bad_pix = np.abs(diffs) > score
        vis = np.abs(diffs)
        vis[m_bad_pix] = -1
        vis = np.ma.masked_array(vis, mask=~mask)
        return score, vis