code: def box_score_fast(self, bitmap, _box):
      h, w = bitmap.shape[:2]
      box = _box.copy()
      xmin = np.clip(np.floor(box[:, 0].min()).astype(np.int), 0, w - 1)
      xmax = np.clip(np.ceil(box[:, 0].max()).astype(np.int), 0, w - 1)
      ymin = np.clip(np.floor(box[:, 1].min()).astype(np.int), 0, h - 1)
      ymax = np.clip(np.ceil(box[:, 1].max()).astype(np.int), 0, h - 1)
  
      mask = np.zeros(
          (ymax - ymin + 1, xmax - xmin + 1), dtype=np.uint8
      )
      box[:, 0] = box[:, 0] - xmin
      box[:, 1] = box[:, 1] - ymin
      cv2.fillPoly(mask, box.reshape(1, -1, 2).astype(np.int32), 1)
      return cv2.mean(bitmap[ymin : ymax + 1, xmin : xmax + 1], mask)[0]
  
file_path: PaddleOCR/benchmark/PaddleOCR_DBNet/post_processing/seg_detector_representer.py
imports: import cv2
  import numpy
  import pyclipper
  import paddle
  from shapely.geometry import Polygon
label_desc: Use image node_id 8 for calling the SegDetectorRepresenter obj's underlying member method code with example usage: obj.box_score_fast(bitmap, _box) and returns: cv2