class_docstr: This is the object detection class for images in the ImageAI library. It provides support for RetinaNet
      , YOLOv3 and TinyYOLOv3 object detection networks . After instantiating this class, you can set it's properties and
  make object detections using it's pre-defined functions.
  
  The following functions are required to be called before object detection can be made
  * setModelPath()
  * At least of of the following and it must correspond to the model set in the setModelPath()
  [setModelTypeAsRetinaNet(), setModelTypeAsYOLOv3(), setModelTypeAsTinyYOLOv3()]
  * loadModel() [This must be called once only before performing object detection]
  
  Once the above functions have been called, you can call the detectObjectsFromImage() function of
  the object detection instance object at anytime to obtain observable objects in any image.
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docstr: 'setModelPath()' function is required and is used to set the file path to a RetinaNet
   object detection model trained on the COCO dataset.
   :param model_path:
   :return:
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code: def setModelPath(self, model_path):
      """
      'setModelPath()' function is required and is used to set the file path to a RetinaNet
       object detection model trained on the COCO dataset.
       :param model_path:
       :return:
      """
  
      if self.__modelPathAdded == False:
          self.modelPath = model_path
          self.__modelPathAdded = True
  
imports: import cv2
  from imageai.Detection.keras_retinanet import models
  from imageai.Detection.keras_retinanet.utils.image import read_image_bgr, preprocess_image, resize_image
  from imageai.Detection.keras_retinanet.utils.visualization import draw_box, draw_caption
  import matplotlib.pyplot
  import matplotlib.image
  import numpy
  import tensorflow
  import os
  from tensorflow.keras import backend
  from tensorflow.keras.layers import Input
  from PIL import Image
  import colorsys
  import warnings
  from imageai.Detection.YOLO.yolov3 import tiny_yolov3_main, yolov3_main
  from imageai.Detection.YOLO.utils import letterbox_image, yolo_eval, preprocess_input, retrieve_yolo_detections, draw_boxes
label_desc: Use image node_id 5 for calling the ObjectDetection obj's underlying member method code with example usage: obj.setModelPath(model_path) without return types