text: import os, sys
  # Set the ROOT_DIR variable to the root directory of the Mask_RCNN git repo
  ROOT_DIR = '/home/surromind/shmoon/maskrcnn/aktwelve_mask_rcnn/'
  print(ROOT_DIR)
  assert os.path.exists(ROOT_DIR), 'ROOT_DIR does not exist. Did you forget to read the instructions above? ;)'
  sys.path.append(ROOT_DIR) 
  from mrcnn.config import Config
  import mrcnn.utils as utils
  from mrcnn import visualize
  import mrcnn.model as modellib
  
  class CigButtsConfig(Config):
      """Configuration for training on the cigarette butts dataset.
      Derives from the base Config class and overrides values specific
      to the cigarette butts dataset.
      """
      # Give the configuration a recognizable name
      NAME = "cig_butts"
  
      # Train on 1 GPU and 1 image per GPU. Batch size is 1 (GPUs * images/GPU).
      GPU_COUNT = 1
      IMAGES_PER_GPU = 1
  
      # Number of classes (including background)
      NUM_CLASSES = 1 + 1  # background + 1 (cig_butt)
  
      # All of our training images are 512x512
      IMAGE_MIN_DIM = 512
      IMAGE_MAX_DIM = 512
  
      # You can experiment with this number to see if it improves training
      STEPS_PER_EPOCH = 5
  
      # This is how often validation is run. If you are using too much hard drive space
      # on saved models (in the MODEL_DIR), try making this value larger.
      VALIDATION_STEPS = 5
      
      # Matterport originally used resnet101, but I downsized to fit it on my graphics card
      BACKBONE = 'resnet50'
  
      # To be honest, I haven't taken the time to figure out what these do
      RPN_ANCHOR_SCALES = (8, 16, 32, 64, 128)
      TRAIN_ROIS_PER_IMAGE = 32
      MAX_GT_INSTANCES = 50 
      POST_NMS_ROIS_INFERENCE = 500 
      POST_NMS_ROIS_TRAINING = 1000 
  