old_contents: # -*- coding: utf-8 -*-
  
  # Convolutional Neural Network
  MODEL_PATH = './trained_models/'
  IMAGE_PATH = './data/localized_images/'
  # IMAGE_PATH = './data/original_images/'
  IMAGE_SHAPE = (90, 160, 3)
  # IMAGE_SHAPE = (720, 1280, 3)
  BATCH_SIZE = 64
  MAX_STEPS = 1500
  ALPHA = 1e-3
  BETA = 1e-2
  
  # Object Detection
  HAARCASCADE = './app/cv/fishcascade/'
  BOUNDINGBOX = './app/cv/bb/'
  BASE_URL = 'http://image-net.org/api/text/imagenet.synset.geturls?wnid={0}'
  # CV_SAMPLE_PATH = './data/native_cv_samples/'
  CV_SAMPLE_PATH = './data/cv_samples/'
  SYNSET_ID_POS = {
                      'Tuna_Bluefin': 'n02627292',
                      'Tuna_Yellowfin': 'n02627532',
                      'Tuna_Albacore': 'n02627037',
                      'DOL': 'n02581957',
                      'LAG': 'n02545841',
                      'SHA': 'n01484285',
                      'OTHER': 'n02512053'
  }
  SYNSET_ID_NEG = {
                      'ocean': 'n09376198',
                      'people': 'n07942152',
                      'poop deck': 'n03982642',
                      'equipment': 'n03294048',
                      'sea boat': 'n04158807',
                      'waves': 'n13868944'
  }
  SYNSET_NUM_POS = 10
  SYNSET_NUM_NEG = 1e4
  HAARPARAMS = dict(
      scaleFactor=5,
      # 0 minNeighbors 0 so that there is minimum change missing fish.
      minNeighbors=0,
      minSize=(50, 50),
      maxSize=(500, 500)
  )
  
new_contents: # -*- coding: utf-8 -*-
  
  # Convolutional Neural Network
  MODEL_PATH = './trained_models/'
  IMAGE_PATH = './data/localized_images/'
  # IMAGE_PATH = './data/original_images/'
  IMAGE_SHAPE = (90, 160, 3)
  # IMAGE_SHAPE = (720, 1280, 3)
  BATCH_SIZE = 64
  MAX_STEPS = 1500
  ALPHA = 1e-3
  BETA = 1e-2
  
  # Object Detection
  HAARCASCADE = './app/cv/fishcascade/'
  BOUNDINGBOX = './app/cv/bb/'
  BASE_URL = 'http://image-net.org/api/text/imagenet.synset.geturls?wnid={0}'
  # CV_SAMPLE_PATH = './data/native_cv_samples/'
  CV_SAMPLE_PATH = './data/cv_samples/'
  SYNSET_ID_POS = {
                      'Tuna_Bluefin': 'n02627292',
                      'Tuna_Yellowfin': 'n02627532',
                      'Tuna_Albacore': 'n02627037',
                      'DOL': 'n02581957',
                      'LAG': 'n02545841',
                      'SHA': 'n01484285',
                      'OTHER': 'n02512053'
  }
  SYNSET_ID_NEG = {
                      'ocean': 'n09376198',
                      'people': 'n07942152',
                      'poop deck': 'n03982642',
                      'equipment': 'n03294048',
                      'sea boat': 'n04158807',
                      'waves': 'n13868944'
  }
  SYNSET_NUM_POS = 10
  SYNSET_NUM_NEG = 1e4
  HAARPARAMS = dict(
      scaleFactor=6,
      # 0 minNeighbors 0 so that there is minimum change missing fish.
      minNeighbors=2,
      minSize=(50, 50),
      maxSize=(700, 700)
  )
  
subject: adjust app param