code: def extract_feature_image(img, feature_type, feature_coord=None):
      """Extract the haar feature for the current image"""
      ii = integral_image(img)
      return haar_like_feature(
          ii,
          0,
          0,
          ii.shape[0],
          ii.shape[1],
          feature_type=feature_type,
          feature_coord=feature_coord,
      )
  
file_path: scikit-image/doc/examples/applications/plot_haar_extraction_selection_classification.py
imports: from time import time
  import numpy
  import matplotlib.pyplot
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.model_selection import train_test_split
  from sklearn.metrics import roc_auc_score
  from skimage.data import lfw_subset
  from skimage.transform import integral_image
  from skimage.feature import haar_like_feature
  from skimage.feature import haar_like_feature_coord
  from skimage.feature import draw_haar_like_feature
label_desc: Use image node_id 1 for calling a global function with example usage: extract_feature_image(img, feature_type, feature_coord) and returns: haar_like_feature