Face Feature(s) Detection with OpenCV

import cv2


face_cascade = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
eye_cascade = cv2.CascadeClassifier("haarcascade_eye.xml")
smile_cascade = cv2.CascadeClassifier("haarcascade_smile.xml")


cap = cv2.VideoCapture(0)

while True:
    ret, img = cap.read()
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    faces = face_cascade.detectMultiScale(gray, 1.3, 5)
    for (x, y, w, h) in faces:
        cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
        roi_gray = gray[y:y+h, x:x+w]
        roi_color = img[y:y+h, x:x+w]

        smile = smile_cascade.detectMultiScale(
            roi_gray,
            scaleFactor=1.6,
            minNeighbors=35,
            minSize=(25, 25),
            flags=cv2.CASCADE_SCALE_IMAGE
        )

        for (x, y, w, h) in smile:
            print("Smile Detected")
            cv2.rectangle(roi_color, (x, y), (x + w, y + h), (255, 255, 0), 2)

        eyes = eye_cascade.detectMultiScale(roi_gray)
        for (ex, ey, ew, eh) in eyes:
            cv2.rectangle(roi_color, (ex, ey), (ex + ew, ey + eh), (0, 255, 0), 2)

    cv2.imshow('img', img)
    k = cv2.waitKey(30) & 0xff
    if k == 27:
        break

cap.release()
cv2.destroyAllWindows()

^ The above script detects facial features such as face,eyes and smile.There are tons of pre-trained haarcascades available for OpenCV that you can use to detect objects such as Moving cars, traffic signs etc.