code: def _convert_to_int_labels(self, targets):
      for idx, target in enumerate(targets):
          # get all string labels for objects in a single image
          labels_array = target["labels"]
          # convert string labels into one hot encoding
          labels_int_array = [
              self._int_mapping[class_name]
              for class_name in labels_array
          ]
          target["labels"] = torch.tensor(labels_int_array)
  
imports: import os
  import pandas
  import random
  import torch
  import torchvision
  from detecto.config import config
  from detecto.utils import default_transforms, filter_top_predictions, xml_to_csv, _is_iterable, read_image
  from torchvision import transforms
  from torchvision.models.detection.faster_rcnn import FastRCNNPredictor
  from tqdm import tqdm
label_desc: Use image node_id 9 for calling the Model obj's underlying member method code with example usage: obj._convert_to_int_labels(targets) without return types