code: def load_classifiers():
      random_seed = 42
      random.seed(random_seed)
      np.random.seed(random_seed)
  
      classifiers = {
          "SVM": svm.LinearSVC(random_state=random_seed),
          "KNN": KNeighborsClassifier(n_neighbors=7),
          "NN": MLPClassifier(
              activation="relu",
              hidden_layer_sizes=(200,),
              max_iter=10000,
              alpha=1e-4,
              solver="adam",
              verbose=20,
              tol=1e-8,
              random_state=1,
              learning_rate_init=0.0001,
              learning_rate="adaptive",
          ),
      }
      return classifiers, random_seed
  
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 6 for calling a global function with example usage: load_classifiers() and returns: classifiers,  random_seed