OpenCV Python Capture图像，同时在浏览器上流式传输实时视频

Question

我正在编写一个实时面部识别应用程序，该应用程序可以捕获未知的面部，但是图像保存似乎与网络摄像头上的流一起加载。或者，如果对未知的面部识别有任何想法和建议，请推荐。任何想法都欢迎。或实时人脸识别API，可以自定义并扩展到个人安全应用程序中。谢谢

import cv2
import subprocess

faceCascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
recognizer = cv2.face.createLBPHFaceRecognizer()
recognizer.load("trainer/trainer.yml")

font = cv2.FONT_HERSHEY_SIMPLEX

row=['',"Adam","Eve"] #names according to face dataset id

class VideoCamera(object): #for streaming on web
    def __init__(self):
        # Using OpenCV to capture from device 0. If you have trouble capturing
        # from a webcam, comment the line below out and use a video file
        # instead.
    self.video = cv2.VideoCapture(0)
        # If you decide to use video.mp4, you must have this file in the folder
        # as the main.py.
        # self.video = cv2.VideoCapture('video.mp4')

    def __del__(self):
        self.video.release()

    def get_frame(self):

        # We are using Motion JPEG, but OpenCV defaults to capture raw images,
        # so we must encode it into JPEG in order to correctly display the
        # video stream.
        #initiate id counter
        id = 0    

        # Define min window size to be recognized as a face
        minW = 0.1*self.video.get(3)
        minH = 0.1*self.video.get(4)

        ret, img =self.video.read()
        img = cv2.flip(img, 1) # Flip vertically

        gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

        faces = faceCascade.detectMultiScale( 
            gray,
            scaleFactor = 1.2,
            minNeighbors = 5,
            minSize = (int(minW), int(minH)),
           )

        for(x,y,w,h) in faces:

            cv2.rectangle(img, (x,y), (x+w,y+h), (0,255,0), 2)

            id, confidence = recognizer.predict(gray[y:y+h,x:x+w])

            # Check if confidence is less them 100 ==> "0" is perfect match 
            if (confidence < 100):

                name = row[id]
                confidence = "  {0}%".format(round(100 - confidence))
            else:
                name = "unknown" 
                confidence = "  {0}%".format(round(100 - confidence))
                count=0 
                while(True) :
                    count +=1
                    cv2.imwrite("path" + str(count) + ".jpg", gray[y:y+h,x:x+w])
                    cv2.imshow('image', img)
                if count >= 20: 
                    break 

        cv2.putText(img, str(name), (x+5,y-5), font, 1, (255,255,255), 2)
        cv2.putText(image, str(confidence), (x+5,y+h-5), font, 1, (255,255,0), 1)  

        ret, jpeg = cv2.imencode('.jpg', img)
        return jpeg.tobytes()  

我希望获得的是捕获一次被检测到的陌生人的图像，同时我们可以观察网络上的实时流。