class_docstr: Class for loading the COCO dataset meant for the DETR ResNet50 model`.
  
  Implement the necessary methods to load the images, labels and generate model predictions in a format comprehensible
   by deepchecks.
class_docstr_tok: ["Class","for","loading","the","COCO","dataset","meant","for","the","DETR","ResNet50","model","`",".","Implement","the","necessary","methods","to","load","the","images",",","labels","and","generate","model","predictions","in","a","format","comprehensible","by","deepchecks","."]
docstr: Use the pre-built self.label_translation to translate the DETR predictions to YOLO COCO classes.
docstr_tok: ["Use","the","pre-built","self.label_translation","to","translate","the","DETR","predictions","to","YOLO","COCO","classes","."]
code: def _convert_to_80_labels(self, labels):
      """Use the pre-built self.label_translation to translate the DETR predictions to YOLO COCO classes."""
      return torch.Tensor(
          [self.label_translation[label] for label in labels]
      ).reshape((-1, 1))
  
file_path: deepchecks/examples/integrations/hugging_face/deepchecks_hugging_face_tutorial.py
imports: import torch
  from transformers import DetrForObjectDetection
  from typing import Union, List, Iterable
  import numpy
  from deepchecks.vision import VisionData
  import torchvision.transforms
  from deepchecks.vision.datasets.detection import coco_torch
  from deepchecks.vision.datasets.detection import coco_utils
  from deepchecks.vision.vision_data import BatchOutputFormat
  from deepchecks.vision.checks import MeanAveragePrecisionReport
label_desc: Use image node_id 5 for calling the COCODETRData obj's underlying member method code with example usage: obj._convert_to_80_labels(labels) and returns: torch