Python实现人脸识别

识别图片

#coding=utf-8
import requests,cv2
import re
import os
import bs4

#2.读取图片
filename = 'E:/Python/Crawler/faces/face7.jpg'
image = cv2.imread(filename)

#3.加载人脸模型 级联分类器
face_moel = cv2.CascadeClassifier('E:/Python/Crawler/faces/facemodel.xml')

#4.对图片进行灰度处理
gray = cv2.cvtColor(image,cv2.COLOR_RGB2GRAY)

#5.检查人脸
faces = face_moel.detectMultiScale(gray)

#6.标记人脸(椭圆形、三角形、矩形)
for (x,y,w,h) in faces:
    #1.原始图片 2.左上角坐标 3.右下角坐标 4.颜色值 5.线宽
    cv2.rectangle(image,(x,y),(x+w,y+h),(0,255,0),2)

#7.显示图片
cv2.imshow('Jim',image)

#8.暂停窗口
cv2.waitKey(0)

#9.销毁窗口
cv2.destroyAllWindows()

其中模型文件为: 人脸模型facemodel.xml

 摄像头实时识别

#coding=utf-8
import requests,cv2
import re,time
import os
import bs4

#打开摄像头
capture = cv2.VideoCapture(0)

print(type(capture))
print(capture.read())

#导入模型
#face_moel = cv2.CascadeClassifier('')
face_moel = cv2.CascadeClassifier('E:/Python/Crawler/faces/facemodel.xml')

c = 0
#获取摄像头的实时画面
while True:
    #5.读取当前摄像头一帧的画面 true false
    ret,image = capture.read()

    #6.图片灰度处理
    gray = cv2.cvtColor(image,cv2.COLOR_RGB2GRAY)

    #7.人脸检测
    faces = face_moel.detectMultiScale(gray,1.1,3,0,(100,100))

    #8.标记人脸
    for (x, y, w, h) in faces:
        # 1.原始图片 2.左上角坐标 3.右下角坐标 4.颜色值 5.线宽
        cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 5)
        #9.显示图片
        cv2.imshow('image',image)
        #暂停窗口
        if cv2.waitKey(5) & 0xFF == ord('q'):
            break
    #time.sleep(5)


# 11.释放资源
capture.release()

#12.销毁窗口
cv2.destroyAllWindows()

其中模型文件为: 人脸模型facemodel.xml