text: import numpy as np
  from keras import backend as K
  import sys
  import os
  
  
  def main():
      K.set_image_dim_ordering('tf')
      sys.path.append(os.path.join(os.path.dirname(__file__), '..'))
  
      from keras_video_classifier.library.recurrent_networks import VGG16LSTMVideoClassifier
      from keras_video_classifier.library.utility.crime.UCF_Crime_loader import load_ucf, scan_ucf_with_labels
  
      vgg16_include_top = False
      data_dir_path = os.path.join(os.path.dirname(__file__), 'very_large_data')
      model_dir_path = os.path.join(os.path.dirname(__file__), 'models', 'UCF-Anomaly-Detection-Dataset')
      config_file_path = VGG16LSTMVideoClassifier.get_config_file_path(model_dir_path,
                                                                       vgg16_include_top=vgg16_include_top)
      weight_file_path = VGG16LSTMVideoClassifier.get_weight_file_path(model_dir_path,
                                                                       vgg16_include_top=vgg16_include_top)
  
      np.random.seed(42)
  
      load_ucf(data_dir_path)
  
      predictor = VGG16LSTMVideoClassifier()
      predictor.load_model(config_file_path, weight_file_path)
  
      videos = scan_ucf_with_labels(data_dir_path, [label for (label, label_index) in predictor.labels.items()])
  
      video_file_path_list = np.array([file_path for file_path in videos.keys()])
      np.random.shuffle(video_file_path_list)
  
      correct_count = 0
      count = 0
      
      print("Begin Predict Using UCF-CRIME-Model: ")
      for video_file_path in video_file_path_list:
          label = videos[video_file_path]
          predicted_label = predictor.predict(video_file_path)
          print('predicted: ' + predicted_label + ' actual: ' + label)
          correct_count = correct_count + 1 if label == predicted_label else correct_count
          count += 1
          accuracy = correct_count / count
          print('correct_count: ' + str(correct_count) + ' count: ' + str(count))
          print('accuracy: ', accuracy)
  
  
  if __name__ == '__main__':
      main()
  