import cv2
import os
import numpy as npdef take_faces():while True:key = input('请输入文件夹的名字，姓名拼音的缩写，如果输入Q，程序退出!')if key == 'Q':break# 在faces_dynamic下面创建子文件夹os.makedirs('./faces_dymamic/%s' % (key), exist_ok=True)take_photo(key)def load_data():listdir = os.listdir('./faces_dymamic')#列表生成式names = [d for d in listdir if not d.startswith('.')]faces  = []target = [i for i in range(len(names))]*10for dir in names:for i in range(1,11):gray = cv2.imread('./faces_dymamic/%s/%d.jpg'% (dir,i)) #三维图片gray_ = gray[:, :, 0] #二维数组faces.append(gray_)faces = np.asarray(faces)target = np.asarray(target)target.sort()  # 排序return faces,target,namesdef dynamic_recognizer_face(face_recognizer,names):cap = cv2.VideoCapture(0)#人脸检测face_detector = cv2.CascadeClassifier('./haarcascade_frontalface_default.xml')while True:flag,frame = cap.read()if not flag:breakgray = cv2.cvtColor(frame, code=cv2.COLOR_BGR2GRAY)faces = face_detector.detectMultiScale(gray,minNeighbors=5)for x,y,w,h in faces:face = gray[y:y + h, x:x + w]face = cv2.resize(face, dsize=(64, 64))y_,confidence = face_recognizer.predict(face)label = names[y_]print('这个人是：%s.置信度：%0.1f'%(label,confidence))cv2.rectangle(frame,pt1=(x,y),pt2=(x+w,y+h),color=[0,0,255],thickness=2)cv2.putText(frame,text=label,org=(x,y-10),fontFace=cv2.FONT_HERSHEY_SIMPLEX,fontScale=1.5,color=[0,0,255],thickness=2)cv2.imshow('face',frame)key = cv2.waitKey(1000//24)if key == ord('q'):breakcv2.destroyAllWindows()cap.release()if __name__ == '__main__':#2、加载数据，返回目标值faces,target,names  = load_data()#print(faces.shape,target.shape)#3、加载人脸识别算法#face_recognizer = cv2.face.EigenFaceRecognizer_create()#face_recognizer = cv2.face.FisherFaceRecognizer_create()face_recognizer = cv2.face.LBPHFaceRecognizer_create()#4、算法训练，找到目标值之间的规律face_recognizer.train(faces,target)#5、动态加载数据dynamic_recognizer_face(face_recognizer,names )