docstr: reformat results
docstr_tok: ["reformat","results"]
code: def _reformat_results(self, img_id2bbox):
      """reformat results"""
      im_ids = img_id2bbox.keys()
      results = []
      for img_id in im_ids:  # output by original im_id order
          if len(img_id2bbox[img_id]) == 0:
              bbox = np.array(
                  [[-1.0, 0.0, 0.0, 0.0, 0.0, 0.0]]
              )  # edge case: no detections
              bbox_num = np.array([0])
          else:
              # np.array of shape [N, 6], 6 is [label, score, x1, y1, x2, y2]
              bbox = img_id2bbox[img_id]
              bbox_num = np.array([len(bbox)])
          res = dict(
              im_id=np.array([[img_id]]), bbox=bbox, bbox_num=bbox_num
          )
          results.append(res)
      return results
  
imports: import copy
  import math
  import random
  import numpy
  from copy import deepcopy
  from typing import List, Tuple
  from collections import defaultdict
  from .chip_box_utils import nms, transform_chip_boxes2image_boxes
  from .chip_box_utils import find_chips_to_cover_overlaped_boxes
  from .chip_box_utils import transform_chip_box
  from .chip_box_utils import intersection_over_box
label_desc: Use image node_id 24 for calling the AnnoCropper obj's underlying member method code with example usage: obj._reformat_results(img_id2bbox) and returns: results