Face Classroom Sign-in Management System (Summary 4) Real-time data transmission

1. Real-time data transmission

Summary three: face classroom sign-in management system (summary three) Baidu face detection API call

In a real situation, the information collection and transmission of face data should be real-time, instead of transmitting a picture in the form of a dialog box, so we need to associate the data collected by the camera with the sending network request.

Two, the core code

1. The accesstoken value is obtained when the window is created, and the initialization function ( __init__ ) in the myWindow class is added:

   self.get_accesstoken()
   

2. Create a thread class ( detectThread ) to use and execute post requests for face detection

   When sending a network request and waiting for the return result, there will be a certain waiting time, the program will be blocked here, and there will be a certain degree of lag

   Use multithreading to solve the stuck phenomenon

   a.The accesstoken value should be obtained when the object is initialized

       def __init__(self, token):
           super(detectThread, self).__init__()
           self.access_token = token
   

   b.Rewrite the run function (the end of the function execution will represent the end of the thread)

       def run(self):
           print("run")
           self.exec_()
   

   c. Get the picture data of the window at a certain moment and send a network request:

       def detect_data(self, base64_image):
           # 请求地址
           request_url = "https://aip.baidubce.com/rest/2.0/face/v3/detect"
           # 请求参数
           params = {
         
         
               "image": base64_image,
               "image_type": "BASE64",
               "face_field": "age,beauty,gender,glasses,face_type"
           }
           # 获取的access_token
           access_token = self.access_token
           # 合并的网络请求地址
           request_url = request_url + "?access_token=" + access_token
           # 通过json格式请求
           headers = {
         
         'content-type': 'application/json'}
           # 发送网络post请求，就会存在一定的返回结果等待时间，程序就会阻塞，存在一定的卡顿现象
           response = requests.post(request_url, data=params, headers=headers)
           if response:
               data = response.json()
               print(data)
   

   Parameter base64_image : image data at a certain moment passed from the window

   A certain moment refers to the time to send the network, if a network request is sent every 1000ms, the parameters will only be passed every 1000ms

3. Modify the myWindow class

   a. The general flow of real-time transmission of picture data between the main window and the thread

   

   b. Customize a signal and slot

   detect_data_signal = pyqtSignal(str)
   

   c.Create a thread for sending face requests, and associate the custom signal with the detect_data function

       def create_thread(self):
           self.detect_thread = detectThread(self.access_token)
           self.detect_thread.start()
           self.detect_data_signal.connect(self.detect_thread.detect_data)
   

   d.Modify on_actionopen function

       def on_actionopen(self):
           # 启动摄像头
           self.camera_data = camera()
           # 启动定时器，进行定时,每个多长时间获取摄像头信号进行显示
           self.timeshow = QTimer(self)
           self.timeshow.start(50)
           # 计数
           self.count = 0
           # 每隔50毫秒将产生一个信号timeout
           self.timeshow.timeout.connect(self.show_camera)
   
           # 每8000ms调用一次人脸检测
           # 创建检测线程
           self.create_thread()
           # 获取要检测的数据
           self.detection_time = QTimer(self)
           self.detection_time.start(8000)
           self.detection_time.timeout.connect(self.get_cameradata)
   
   

   When you click "Start sign-in", a new thread is created and camera data is obtained every 8000ms (call the get_cameradata function)

   e.Create a new get_cameradata function to obtain camera information and send a custom signal

       def get_cameradata(self):
           # 摄像头获取画面
           camera_img = self.camera_data.read_camera()
           # 把摄像头画面转换成图片
           _, enc = cv2.imencode('.jpg', camera_img)
           # 设置为base64编码格式
           base64_image = base64.b64encode(enc.tobytes())
           # 产生信号，传递数据
           self.detect_data_signal.emit(str(base64_image))
   

Three, the effect is as follows

It can be found that there are still some lags in the middle. The reason is that a signal is generated by the window to directly call the network request detection function ( detect_data ) in the thread.

The results returned are as follows:

{
    
    'error_code': 222203, 'error_msg': 'image check fail', 'log_id': 1545256500165, 'timestamp': 1603251891, 'cached': 0, 'result': None}

There is a return result, indicating that there is no problem with network communication in this way. The error in the returned result is due to an error in the base64_image format. At the same time, there are still some small problems, save it for the next summary!

Summary 5 Portal: Face Classroom Sign-in Management System (Summary 5) Solve the problem of screen freeze