text: import numpy as np
  import pandas as pd
  import cv2, os
  from keras.models import load_model
  import utils
  
  # Constant
  os.environ["CUDA_VISIBLE_DEVICES"] = "3"
  BATCH_SIZE = 12
  
  # load data
  Dir = './imgs'
  fo = pd.read_csv('./imgs/labels.csv')
  ftest = fo.values
  te_num = ftest.shape[0]
  
  # test
  images, labels, bvalues, id_values, imgname = utils.batch_test(ftest, Dir, batch_size = BATCH_SIZE)
  
  # load model
  model = load_model('./model/model.h5', custom_objects={'loss_imgset_fn': utils.loss_imgset(id_values, BATCH_SIZE)})
  results = model.predict(images, batch_size=BATCH_SIZE, verbose=1)
  pbilvalues = np.squeeze(results[1])
  dataframe = pd.DataFrame({'ID':id_values, 'imgname':imgname, 'pbil_value':pbilvalues})
  dataframe.to_csv('./res.csv')
  print("done")
  