code: def __init__(self, labels):
      self.__labels = labels
      self.__colors = []
  
      for i in range(len(labels)):
          color_space_values = np.random.randint(50, 255, size=(3,))
          red, green, blue = color_space_values
          red, green, blue = int(red), int(green), int(blue)
          self.__colors.append([red, green, blue])
  
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 1 to create a new CustomDetectionUtils object  with example: obj = CustomDetectionUtils(labels)