from __future__ import print_function import cv2 as cv import argparse def detectAndDisplay(frame): frame_gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY) frame_gray = cv.equalizeHist(frame_gray) #-- Detect faces faces = face_cascade.detectMultiScale(frame_gray) for (x,y,w,h) in faces: center = (x + w//2, y + h//2) frame = cv.ellipse(frame, center, (w//2, h//2), 0, 0, 360, (255, 0, 255), 4) faceROI = frame_gray[y:y+h,x:x+w] #-- In each face, detect eyes eyes = eyes_cascade.detectMultiScale(faceROI) for (x2,y2,w2,h2) in eyes: eye_center = (x + x2 + w2//2, y + y2 + h2//2) radius = int(round((w2 + h2)*0.25)) frame = cv.circle(frame, eye_center, radius, (255, 0, 0 ), 4) cv.imshow('Capture - Face detection', frame) parser = argparse.ArgumentParser(description='Code for Cascade Classifier tutorial.') parser.add_argument('--face_cascade', help='Path to face cascade.', default='data/haarcascades/haarcascade_frontalface_alt.xml') parser.add_argument('--eyes_cascade', help='Path to eyes cascade.', default='data/haarcascades/haarcascade_eye_tree_eyeglasses.xml') parser.add_argument('--camera', help='Camera divide number.', type=int, default=0) args = parser.parse_args() face_cascade_name = args.face_cascade eyes_cascade_name = args.eyes_cascade face_cascade = cv.CascadeClassifier() eyes_cascade = cv.CascadeClassifier() #-- 1. Load the cascades if not face_cascade.load(cv.samples.findFile(face_cascade_name)): print('--(!)Error loading face cascade') exit(0) if not eyes_cascade.load(cv.samples.findFile(eyes_cascade_name)): print('--(!)Error loading eyes cascade') exit(0) camera_device = args.camera #-- 2. Read the video stream cap = cv.VideoCapture(camera_device) if not cap.isOpened: print('--(!)Error opening video capture') exit(0) while True: ret, frame = cap.read() if frame is None: print('--(!) No captured frame -- Break!') break detectAndDisplay(frame) if cv.waitKey(10) == 27: break