class_docstr: This is the object detection class for videos and camera live stream inputs using your custom trained detection models. It provides support for your custom YOLOv3 models.
docstr: 'loadModel' is used to load the model into the CustomVideoObjectDetection class
  
  :return:
docstr_tok: ["'loadModel","'","is","used","to","load","the","model","into","the","CustomVideoObjectDetection","class",":","return",":"]
code: def loadModel(self):
      """
      'loadModel' is used to load the model into the CustomVideoObjectDetection class
  
      :return:
      """
  
      if self.__model_loaded == False:
          if self.__model_type == "yolov3":
              detector = CustomObjectDetection()
              detector.setModelTypeAsYOLOv3()
              detector.setModelPath(self.__model_path)
              detector.setJsonPath(self.__detection_config_json_path)
              detector.loadModel()
  
              self.__detector = detector
              self.__model_loaded = True
  
imports: import os
  import re
  import numpy
  import json
  from imageai.Detection.Custom.voc import parse_voc_annotation
  from imageai.Detection.YOLO.yolov3 import yolov3_main, yolov3_train, dummy_loss
  from imageai.Detection.Custom.generator import BatchGenerator
  from imageai.Detection.Custom.utils.utils import normalize, evaluate, makedirs
  from tensorflow.keras.callbacks import ReduceLROnPlateau
  from tensorflow.keras.optimizers import Adam
  from imageai.Detection.Custom.callbacks import CustomModelCheckpoint
  from imageai.Detection.Custom.utils.multi_gpu_model import multi_gpu_model
  from imageai.Detection.Custom.gen_anchors import generateAnchors
  import tensorflow
  from tensorflow.keras.models import load_model
  from tensorflow.keras import Input
  from tensorflow.keras.callbacks import TensorBoard
  import tensorflow.keras.backend
  import cv2
label_desc: Use image node_id 5 for calling the CustomVideoObjectDetection obj's underlying member method code with example usage: obj.loadModel() without return types