code: def _generate_predict_luminoth_config(self, **kwargs):
      if self.algorithm is None:
          with open(f"{self.model_path}/luminoth.yml") as f:
              config = yaml.load(f)
  
          self.algorithm = config["model"]["type"]
  
      config = {
          "train": {
              "run_name": self.name,
              "job_dir": self.model_path.replace(f"/{self.name}", ""),
          },
          "dataset": {
              "type": "object_detection",
              "dir": self.model_path,
          },
          "model": {
              "type": self.algorithm,
              "network": {"num_classes": len(self.classes)},
          },
      }
  
      with open(f"{self.model_path}/luminoth.predict.yml", "w") as f:
          f.write(yaml.dump(config))
  
imports: import os
  import yaml
  import json
  import subprocess
  import shlex
  import time
  import tensorflow
  from luminoth.tools.dataset.readers.object_detection import ObjectDetectionReader
  from luminoth.tools.dataset.writers.object_detection_writer import ObjectDetectionWriter
  from luminoth.tools.checkpoint import get_checkpoint_config
  from luminoth.utils.dataset import read_xml, read_image
  from luminoth.utils.config import get_config
  from luminoth.utils.predicting import PredictorNetwork
  from luminoth.train import run
  from luminoth.predict import predict_image
  from serpent.machine_learning.object_recognition.object_recognizer import ObjectRecognizer
  from serpent.utilities import SerpentError
label_desc: Use image node_id 8 for calling the LuminothObjectRecognizer obj's underlying member method code with example usage: obj._generate_predict_luminoth_config() without return types