python+opencv+face_recognition實現門禁系統

# 信息採集
def face_c():
    import cv2 
    capture =cv2.VideoCapture(0)
    cv2.namedWindow("camera",1)
    print("採集圖片 識別成功後按空格鍵保存圖片")

    font = cv2.FONT_HERSHEY_PLAIN
    max_ = 0
    face=[]
    while True:
        ret, img = capture.read()
        face_cascade = cv2.CascadeClassifier("./face.xml")
        if img.ndim == 3:
            gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
        else:
            gray = img
        faces = face_cascade.detectMultiScale(gray)
        for (x,y,width,height) in faces:
            if (width*height)>max_:
                max_ = width*height
                face = [x,y,x+width,y+height]
        if max_ != 0:
            img_ = cv2.rectangle(img, (face[0],face[1]), (face[2],face[3]), (255,0,0), 4)
            max_ = 0
        cv2.imshow('camera',img_)
        key = cv2.waitKey(3)
        if key == 27:
            #esc鍵退出
            print("esc break...")
            cv2.destroyAllWindows() 
            capture.release()
            break
        if key == ord(' '):
            # 保存一張圖像
            cv2.destroyAllWindows() 
            capture.release()
            gray = gray[face[1]-100:face[3]+100, face[0]-100:face[2]+100]
            path = input("請輸入姓名")
            cv2.imwrite('./img/'+path+'.jpg',gray)
            break
def face_s():
    import face_recognition
    import os 
    import cv2 
    IP = input("請輸入IP地址，輸入0用電腦攝像頭")
    if IP == '0':
        capture =cv2.VideoCapture(0)
    else:
        capture =cv2.VideoCapture(IP)
    cv2.namedWindow("camera",1)
    font = cv2.FONT_HERSHEY_PLAIN
    max_ = 0
    face=[]
    face_img = {}
    flag=0
    text = ""
    g = os.walk(r"./img")  

    for path,dir_list,file_list in g:  
        for file_name in file_list:  

            print('讀取到'+ os.path.join(path, file_name) )
            picture  = face_recognition.load_image_file(os.path.join(path, file_name))
            face_img[file_name[:-4]] = face_recognition.face_encodings(picture)[0]
    while True:
        ret, img = capture.read()
        face_cascade = cv2.CascadeClassifier("./face.xml")#此處需要將模型在電腦中搜索並複製到和代碼同目錄下
        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
        faces = face_cascade.detectMultiScale(gray)
        for (x,y,width,height) in faces:
            if (width*height)>max_:
                max_ = width*height
                face = [x,y,x+width,y+height]
        if max_ != 0:
            img = cv2.rectangle(img, (face[0],face[1]), (face[2],face[3]), (255,0,0), 4)
            cv2.putText(img, text, (face[0], face[1]), font, 2, (0,0,255), 1)
            flag =(flag+1)%10
            if flag == 0:
                try:
                    face_gray = face_recognition.face_encodings(img)[0]
                    for i in face_img:
                        results = face_recognition.compare_faces([face_img[i]], face_gray,tolerance=0.4)
                        if results[0] == True:
                            text = i
                            break
                        else:
                            text = ''
                except  BaseException:
                    pass
            max_ = 0
        cv2.imshow('camera',img)
        key = cv2.waitKey(3)
        if key == 27:
            #esc鍵退出
            cv2.destroyAllWindows() 
            capture.release()
            break
while(True):
    print("請選擇模式")
    print("1 信息採集")
    print("2 實時識別")
    print("q 退出")
    a = input()
    if a=='1':
        face_c()
    elif a=='2':
        face_s()
    elif a=='q':
        break
    else:
        print("輸入信息不對請重新輸入")