基于python的OpenCV人脸识别模型

import numpy as np
import cv2

# 人脸识别分类器
faceCascade = cv2.CascadeClassifier(r'haarcascade_frontalface_default.xml')

# 识别眼睛的分类器
eyeCascade = cv2.CascadeClassifier(r'haarcascade_eye.xml')

# 开启摄像头
cap = cv2.VideoCapture(0)
ok = True

while ok:
    # 读取摄像头中的图像，ok为是否读取成功的判断参数
    ok, img = cap.read()
    # 转换成灰度图像
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

    # 人脸检测
    faces = faceCascade.detectMultiScale(
        gray,
        scaleFactor=1.2,
        minNeighbors=5,
        minSize=(32, 32)
    )

    # 在检测人脸的基础上检测眼睛
    for (x, y, w, h) in faces:
        fac_gray = gray[y: (y + h), x: (x + w)]
        result = []
        eyes = eyeCascade.detectMultiScale(fac_gray, 1.3, 2)

        # 眼睛坐标的换算，将相对位置换成绝对位置
        for (ex, ey, ew, eh) in eyes:
            result.append((x + ex, y + ey, ew, eh))

    # 画矩形
    for (x, y, w, h) in faces:
        cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)

    for (ex, ey, ew, eh) in result:
        cv2.rectangle(img, (ex, ey), (ex + ew, ey + eh), (0, 255, 0), 2)

    cv2.imshow('video', img)

    k = cv2.waitKey(1)
    if k == 27:  # press 'ESC' to quit
        break

cap.release()
cv2.destroyAllWindows()