python + opencv图像处理——人脸检测

HAAR和LBP数据
这是我使用的两个数据
链接：https://pan.baidu.com/s/1_JADYabXD1aUs_fHCH9YEQ
提取码：wj6g
复制这段内容后打开百度网盘手机App，操作更方便哦

from matplotlib import pyplot as plt 
from cv2 import cv2 as cv
import numpy as np 

#opencv基于HAAR实现人脸检测
def face_detect_HAAR(image):
    #转换成灰度图像
    gray =cv.cvtColor(image,cv.COLOR_BGR2GRAY)
    #人脸识别器分类器
    face_detetor = cv.CascadeClassifier('C:\\ruanjian\\model\\opencv-master\\data\\haarcascades\\haarcascade_frontalface_alt_tree.xml')
    #在多个尺度空间对其进行人脸检测
    faces = face_detetor.detectMultiScale(gray,1.02,3)
    #faces = face_detetor.detectMultiScale(gray,scaleFactor=1.2,minNeighbors=3,minSize=(32,32))
    for x,y,w,h in faces:
        cv.rectangle(image,(x,y),(x+w,y+h),(0,0,255),2)#颜色，线宽

    cv.imshow('face_detect_demo',image)

#opencv基于LBP实现人脸检测
def face_detect_LBP(image):
    #转换成灰度图像
    gray =cv.cvtColor(image,cv.COLOR_BGR2GRAY)
    #人脸识别器分类器
    face_detetor = cv.CascadeClassifier('C:\\ruanjian\\model\\opencv-master\\data\\lbpcascades\\lbpcascade_frontalcatface.xml')
    #在多个尺度空间对其进行人脸检测
    faces = face_detetor.detectMultiScale(gray,1.1,2)#后两个参数进行调整
    #faces = face_detetor.detectMultiScale(gray,scaleFactor=1.2,minNeighbors=3,minSize=(32,32))
    for x,y,w,h in faces:
        cv.rectangle(image,(x,y),(x+w,y+h),(0,0,255),2)#颜色，线宽

    cv.imshow('face_detect_demo',image)


if __name__ == "__main__":
    filepath = "C:\\pictures\\7.jpg"
    img = cv.imread(filepath)       # blue green red
    #试一下视频
    capture = cv.VideoCapture(0)#自己的摄像头
    while True:
        ret,frame = capture.read()
        frame = cv.flip(frame,1)#镜像
        face_detect_HAAR(frame)
        c = cv.waitKey(10)
        if c == 27:#ESC
            break
    cv.namedWindow("input image",cv.WINDOW_AUTOSIZE)
    cv.imshow("input image",img)
    #face_detect_demo()

    cv.waitKey(0)
    cv.destroyAllWindows()