code: def extract_features(img, feature_set="raw"):
      if feature_set == "hog":
          return extract_hog_features(img)
      elif feature_set == "raw":
          return extract_raw_pixels(img)
      else:
          return extract_hsv_histogram(img)
  
file_path: Mozart/src/train.py
imports: import cv2
  import random
  import imutils
  from glob import glob
  from sklearn.model_selection import train_test_split
  from sklearn.neighbors import KNeighborsClassifier
  from sklearn.neural_network import MLPClassifier
  from sklearn import svm
  import numpy
  import matplotlib.pyplot
  import pickle
label_desc: Use image node_id 4 for calling a global function with example usage: extract_features(img, feature_set) and returns: extract_hog_features, extract_raw_pixels, extract_hsv_histogram