code: def __init__(
      self,
      name,
      algorithm="ssd",
      classes=None,
      model_path=None,
      **kwargs,
  ):
      self.name = name
  
      self.model_path = model_path
      self.model = None
  
      if self.model_path is not None:
          self.classes = self._load_classes()
  
          self.algorithm = None
          self.model = self._load_model()
      else:
          if algorithm not in self.__class__.algorithms:
              raise SerpentError(
                  f"Algorithm '{algorithm}' not implemented in {self.__class__.__name__}"
              )
  
          self.algorithm = algorithm
          self.classes = classes
  
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 1 to create a new LuminothObjectRecognizer object from inherited base classes: ObjectRecognizer with example: obj = LuminothObjectRecognizer(name, algorithm, classes, model_path)