text: from __future__ import print_function
  from pyAudioAnalysis import audioBasicIO
  from pyAudioAnalysis import MidTermFeatures
  from pyAudioAnalysis import audioTrainTest as aT
  from pyAudioAnalysis import audioSegmentation as aS
  import matplotlib.pyplot as plt
  import argparse
  
  def parseArguments():
      parser = argparse.ArgumentParser(prog='PROG')
      parser.add_argument('-d' , '--data_folder', nargs=None, default="/Users/tyiannak/ResearchData/Audio Dataset/pyAudioAnalysisData/")
      parser.add_argument('-c' , '--classifier_type', nargs=None, required=True, 
                          choices = ["knn", "svm", "svm_rbf", "randomforest", "extratrees", "gradientboosting"],
                          help="Classifier type")
      args = parser.parse_args()        
      return args
  
  
  
  if __name__ == '__main__':
      args = parseArguments()
      root_data_path = args.data_folder
      classifier_type = args.classifier_type
      classifier_path = "sm_" + classifier_type
      aT.featureAndTrain([root_data_path +"SM/speech",root_data_path + "SM/music"], 
                         1.0, 1.0, 0.2, 0.2, classifier_type, 
                         classifier_path, False)
  