code: def extract_hsv_histogram(img):
      resized = cv2.resize(img, target_img_size)
      hsv = cv2.cvtColor(resized, cv2.COLOR_BGR2HSV)
      hist = cv2.calcHist(
          [hsv], [0, 1, 2], None, [8, 8, 8], [0, 180, 0, 256, 0, 256]
      )
      if imutils.is_cv2():
          hist = cv2.normalize(hist)
      else:
          cv2.normalize(hist, hist)
      return hist.flatten()
  
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 2 for calling a global function with example usage: extract_hsv_histogram(img) and returns: hist