人脸识别之成果检验（四）

读取训练好的数据----->得到人脸对应的id----->人脸识别
代码：

import cv2
import os


# 加载训练数据集文件
recogizer = cv2.face.LBPHFaceRecognizer_create()
recogizer.read('trainer/trainer.yml')
names = []
warningtime = 0

def face_detect(img):
    '''
    进行人脸识别
    :param img:
    :return:
    '''
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)    # 转换为灰度
    face_detector = cv2.CascadeClassifier('D:/opencv(WIN)/opencv/sources/data/haarcascades/haarcascade_frontalface_alt2.xml')
    face = face_detector.detectMultiScale(gray,1.1,5,cv2.CASCADE_SCALE_IMAGE,(100,100),(300,300))
    for x, y, w, h in face:
        cv2.rectangle(img, (x,y), (x+w,y+h), color=(0,0,255), thickness=2)
        cv2.circle(img, center=(x+w//2,y+h//2), radius=w//2, color=(0,255,0), thickness=1)
        # 人脸识别
        ids, confidence = recogizer.predict(gray[y:y + h, x:x + w])
        if confidence > 80:
            global warningtime
            warningtime += 1
            if warningtime > 100:
               warningtime = 0
            cv2.putText(img, 'unkonw', (x + 10, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (0, 255, 0), 1)
        else:
            cv2.putText(img,str(names[ids-1]), (x + 10, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (0, 255, 0), 1)
    cv2.imshow('result',img)

def name():
    '''
    得到人脸对应的id
    :return:
    '''
    path = 'D:/Pycharm/other/TEST/'
    names = []
    imagePaths=[os.path.join(path,f) for f in os.listdir(path)]
    for imagePath in imagePaths:
       name = str(os.path.split(imagePath)[1].split('.')[0])
       names.append(name)


if __name__ == '__main__':
    cap = cv2.VideoCapture(0)    # 电脑摄像头开启，检测自己的人脸
    # cap = cv2.VideoCapture('1.mp4')    # 检测视频的人脸
    name()
    while True:
        flag, frame = cap.read()
        if not flag:
            break
        face_detect(frame)
        if ord(' ') == cv2.waitKey(10):
            break
    cv2.destroyAllWindows()
    cap.release()