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: 'setJsonPath' is used to set the filepath to the configuration JSON file for your custom detection model
  
  :param configuration_json:
  :return:
docstr_tok: ["'setJsonPath","'","is","used","to","set","the","filepath","to","the","configuration","JSON","file","for","your","custom","detection","model",":","param","configuration_json",":",":","return",":"]
code: def setJsonPath(self, configuration_json):
      """
      'setJsonPath' is used to set the filepath to the configuration JSON file for your custom detection model
  
      :param configuration_json:
      :return:
      """
      self.__detection_config_json_path = configuration_json
  
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 4 for calling the CustomVideoObjectDetection obj's underlying member method code with example usage: obj.setJsonPath(configuration_json) without return types