code: def prepare_boxlist(self, boxes, scores, image_shape):
          
          boxes = boxes.reshape(-1, 4)
          scores = scores.reshape(-1)
          boxlist = BoxList(boxes, image_shape, mode="xyxy")
          boxlist.add_field("scores", scores)
          return boxlist
docs: Returns BoxList from `boxes` and adds probability scores information
          as an extra field
          `boxes` has shape (#detections, 4 * #classes), where each row represents
          a list of predicted bounding boxes for each of the object classes in the
          dataset (including the background class). The detections in each row
          originate from the same object proposal.
          `scores` has shape (#detection, #classes), where each row represents a list
          of object detection confidence scores for each of the object classes in the
          dataset (including the background class). `scores[i, j]`` corresponds to the
          box at `boxes[i, j * 4:(j + 1) * 4]`.