code: def load_annotation(self, i):
      annots = []
  
      for obj in self.instances[i]["object"]:
          annot = [
              obj["xmin"],
              obj["ymin"],
              obj["xmax"],
              obj["ymax"],
              self.labels.index(obj["name"]),
          ]
          annots += [annot]
  
      if len(annots) == 0:
          annots = [[]]
  
      return np.array(annots)
  
file_path: ImageAI/imageai_tf_deprecated/Detection/Custom/generator.py
imports: import cv2
  import copy
  import numpy
  from tensorflow.keras.utils import Sequence
  from imageai.Detection.Custom.utils.bbox import BoundBox, bbox_iou
  from imageai.Detection.Custom.utils.image import apply_random_scale_and_crop, random_distort_image, random_flip, correct_bounding_boxes
label_desc: Use image node_id 10 for calling the BatchGenerator obj's underlying member method code with example usage: obj.load_annotation(i) and returns: np