Now that we understand how to detect faces, we can generalize the concept to detect other body parts too. It's important to understand that the Viola-Jones framework can be applied to any object. The accuracy and robustness will depend on the uniqueness of the object. For example, a human face has very unique characteristics, so it's easy to train our system to be robust. On the other hand, objects like towels, clothes or books are too generic, and there are no distinguishing characteristics as such, so it's more difficult to build a robust detector.
Let's see how to build an eye detector:
import cv2
import numpy as np
face_cascade = cv2.CascadeClassifier('./cascade_files/haarcascade_frontalface_alt.xml')
eye_cascade = cv2.CascadeClassifier('./cascade_files/haarcascade_eye.xml')
if face_cascade.empty():
raise IOError('Unable to load the face cascade classifier xml file')
if eye_cascade.empty():
raise IOError('Unable to load the eye cascade classifier xml file...