opencv级联分类器实现人脸识别

级联分类器（Cascade Classifier）是一种基于Haar特征的对象检测算法，首先需要手动的去训练自己的模型，如人脸识别官网有训练好的，可以直接拿来用
链接直达

官方代码示例：

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)
    # -- 检测面部
    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]
        # -- 在每张面部上检测眼睛
        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='haarcascade_frontalface_alt.xml')
parser.add_argument('--eyes_cascade', help='Path to eyes cascade.', default='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. 加载级联
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. 读取视频流
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