def METHOD_NAME(img_seg_result=None,
                           class_names=None,
                           score_thr=0.3):
    assert img_seg_result is not None, 'img_seg_result should be not None.'
    assert class_names is not None, 'class_names should be not None.'
    img_seg_result = get_img_seg_results(
        det_rawdata=(img_seg_result[0], img_seg_result[1]),
        class_names=class_names,
        score_thr=score_thr,
        is_decode=False)
    results_dict = {
        OutputKeys.BOXES: [],
        OutputKeys.MASKS: [],
        OutputKeys.LABELS: [],
        OutputKeys.SCORES: []
    }
    for seg_result in img_seg_result:
        box = [
            int(seg_result[0]),
            int(seg_result[1]),
            int(seg_result[2]),
            int(seg_result[3])
        ]
        score = float(seg_result[4])
        category = seg_result[5]
        mask = np.array(seg_result[6], order='F', dtype='uint8')
        mask = mask.astype(float)
        results_dict[OutputKeys.BOXES].append(box)
        results_dict[OutputKeys.MASKS].append(mask)
        results_dict[OutputKeys.SCORES].append(score)
        results_dict[OutputKeys.LABELS].append(category)
    return results_dict