opencv基于Haar人脸检测和眼睛检测

from __future__ import print_function
import cv2 as cv
import argparse
def detectAndDisplay(frame):
    frame_gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)#灰度处理
    frame_gray = cv.equalizeHist(frame_gray)#直方图均衡化
    #-- Detect faces
    faces = face_cascade.detectMultiScale(frame_gray)
    for (x,y,w,h) in faces:
        center = (x + w//2, y + h//2)#获取方框中心位置
        frame = cv.ellipse(frame, center, (w//2, h//2), 0, 0, 360, (255, 0, 255), 4)#画椭圆
        faceROI = frame_gray[y:y+h,x:x+w]#获取感兴趣的区域，即人脸矩形
        #-- 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)#获取眼睛中心
            radius = int(round((w2 + h2)*0.25))#获取半径
            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='haarcascades/haarcascade_frontalface_alt.xml')
parser.add_argument('--eyes_cascade', help='Path to eyes cascade.', default='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