code: def deepchecks_map(model):
      def _deepchecks_map(image, label):
          pred = _prediction_to_deepchecks_format(model, image)
          # class_id is required to be the first column
          label = (
              tf.gather(label, [4, 0, 1, 2, 3], axis=1)
              if label is not None and len(label) > 0
              else label
          )
          return {
              "images": [image],
              "labels": [label],
              "predictions": [pred],
          }
  
      return _deepchecks_map
  
file_path: deepchecks/deepchecks/vision/datasets/detection/coco_tensorflow.py
imports: import os
  import typing
  from pathlib import Path
  import albumentations
  import numpy
  from typing_extensions import Literal
  from deepchecks import vision
  from deepchecks.vision.datasets.detection.coco_utils import COCO_DIR, LABEL_MAP, download_coco128, get_image_and_label
  from deepchecks.vision.vision_data import VisionData
label_desc: Use image node_id 3 for calling a global function with example usage: deepchecks_map(model) and returns: _deepchecks_map, dict