人脸识别python

在Python中，可以使用多种开源的人脸识别库来实现人脸识别，其中比较常用的有OpenCV和Dlib等。

使用OpenCV进行人脸识别的步骤如下：

1. 安装OpenCV库

pip install opencv-python

2. 加载人脸检测器和人脸识别器模型

import cv2
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
recognizer = cv2.face.LBPHFaceRecognizer_create()
recognizer.read('trainer.yml')

3. 打开摄像头，读取视频流

cap = cv2.VideoCapture(0)
while True:
    ret, img = cap.read()
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

4. 进行人脸检测

faces = face_cascade.detectMultiScale(gray, scaleFactor=1.2, minNeighbors=5)

5. 对每张检测到的人脸进行识别

for (x,y,w,h) in faces:
    roi_gray = gray[y:y+h, x:x+w]
    id_, conf = recognizer.predict(roi_gray)
    if conf>=45 and conf<=85:
        # 在图像中绘制人脸和对应的识别结果
        cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),2)
        cv2.putText(img, labels[id_], (x,y-10), cv2.FONT_HERSHEY_SIMPLEX, 1, (0,255,0), 2, cv2.LINE_AA)

完整代码示例：

import cv2

face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
recognizer = cv2.face.LBPHFaceRecognizer_create()
recognizer.read('trainer.yml')

labels = {"person_name": 1}

cap = cv2.VideoCapture(0)

while True:
    ret, img = cap.read()
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    faces = face_cascade.detectMultiScale(gray, scaleFactor=1.2, minNeighbors=5)
    for (x,y,w,h) in faces:
        roi_gray = gray[y:y+h, x:x+w]
        id_, conf = recognizer.predict(roi_gray)
        if conf>=45 and conf<=85:
            cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),2)
            cv2.putText(img, labels[id_], (x,y-10), cv2.FONT_HERSHEY_SIMPLEX, 1, (0,255,0), 2, cv2.LINE_AA)
    cv2.imshow('img',img)
    k = cv2.waitKey(30) & 0xff
    if k == 27:
        break

cap.release()
cv2.destroyAllWindows()