code: def __call__(self, data) -> Tuple[Any, Any]:
      loglevel = data.get("logging", "INFO").upper()
      logger.setLevel(loglevel)
  
      output = data.get(self.key_output_format, "slicer")
      logger.info(f"+++ Output Type: {output}")
  
      output_json = data.get(self.json, {})
      write_to_file = data.get(self.key_write_to_file, True)
      if not write_to_file:
          return None, output_json
  
      res_json = {
          "name": f"MONAILabel Annotations - {data.get('model')}",
          "description": data.get("description"),
          "model": data.get("model"),
          "location": data.get("location"),
          "size": data.get("size"),
          "box": data.get(self.pred_box_key).cpu().detach().tolist(),
          "label": data.get(self.pred_label_key)
          .cpu()
          .detach()
          .tolist(),
          "image": data.get("image_path", None),
          "latencies": data.get("latencies"),
      }
  
      output_files = None
  
      if output == "slicer":
          logger.info(
              "+++ Generating Slicer Detection ROI Node JSON file"
          )
          output_files, _ = create_slicer_detection_json(
              res_json, loglevel=loglevel
          )
      else:
          logger.info("+++ Return Default JSON Annotation")
  
      return output_files, res_json
  
imports: import logging
  import tempfile
  from typing import Any, Dict, Iterable, List, Optional, Tuple
  import itk
  import nrrd
  import numpy
  import torch
  from monai.data import MetaTensor
  from monai.data.image_writer import NibabelWriter
  from monailabel.utils.others.detection import create_slicer_detection_json
  from monailabel.utils.others.generic import file_ext
  from monailabel.utils.others.pathology import create_asap_annotations_xml, create_dsa_annotations_json
label_desc: Use image node_id 2 for calling the DetectionWriter obj's underlying member method code with example usage: obj.__call__(data) and returns: output_files,  res_json, None,  output_json