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]`.

def prepare_boxlist(self, boxes, scores, image_shape):
        """
        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]`.
        """
        boxes = boxes.reshape(-1, 4)
        scores = scores.reshape(-1)
        boxlist = BoxList(boxes, image_shape, mode="xyxy")
        boxlist.add_field("scores", scores)
        return boxlist