Raspberry PI上的多处理Python程序-未调用异步函数

在我当前的项目中，当我发送停止信号（程序在我的计算机上运行）时，我试图停止视频流（程序在Raspberry PI上运行）

为了实现这个目标，我编写了一个多处理python代码，它运行两个进程

• 过程1从装有覆盆子PI的摄像头读取数据，并将其发送到亚马逊Kinesis。它使用树莓PI的

  OpenCV

  库将图像发送到Kinesis

• 进程2是一个用户（通过AWS物联网），它等待来自AWS物联网的停止信号。当接收到停止信号时，停止流媒体

我使用了

commandFlag

作为标志。它是用

0

初始化的。每当线程2接收到停止信号时，

commandFlag

就会转到

1

在当前程序中，

def on_message（client，userdata，msg）：

不被调用。因此，它没有停止视频流（因为

commandFlag

标志未设置为

1

）

此外，它不会释放连接的相机资源

你能建议其他解决这个问题的方法吗？我是否需要在程序中进行任何其他更改才能正常工作

  import sys
import cPickle
import datetime
import cv2
import boto3
import time
import cPickle
from multiprocessing import Pool
import pytz
import threading
import multiprocessing

#Subscriber
import paho.mqtt.client as paho
import os
import socket
import ssl

commandFlag = 0



# The unique hostname that &IoT; generated for this device.
awshost = "AAAAAA-ats.iot.us-east-1.amazonaws.com"
awsport = 8883

# A programmatic shadow handler name prefix.
clientId = "IoTDevice"
thingName = "IoTDevice"

# The relative path to the correct root CA file for &IoT;, which you have already saved onto this device.
caPath = "AmazonRootCA1.pem"

# The relative path to your certificate file that 
# &IoT; generated for this device, which you 
# have already saved onto this device.
certPath = "AAAAA-certificate.pem.crt"


# The relative path to your private key file that 
# &IoT; generated for this device, which you 
# have already saved onto this device.
keyPath = "AAAAAA-private.pem.key"


kinesis_client = boto3.client("kinesis", region_name='us-east-1')
rekog_client = boto3.client("rekognition",region_name='us-east-1')

camera_index = 0 # 0 is usually the built-in webcam
capture_rate = 30 # Frame capture rate.. every X frames. Positive integer.
rekog_max_labels = 123
rekog_min_conf = 50.0

def on_connect(client, userdata, flags, rc):
    global commandFlag
    print("I am ready to receive control message...." )
    client.subscribe("#" , 1 )

def on_message(client, userdata, msg):
    global commandFlag
    print("Received Switch Off message from AWS IoT....")
    commandFlag = 1


def subscriber():
    global commandFlag
    mqttc = paho.Client()
    mqttc.on_connect = on_connect
    mqttc.on_message = on_message
    mqttc.tls_set(caPath, certfile=certPath, keyfile=keyPath, cert_reqs=ssl.CERT_REQUIRED, tls_version=ssl.PROTOCOL_TLSv1_2, ciphers=None)
    mqttc.connect(awshost, awsport, keepalive=60)
    mqttc.loop_forever()

#Send frame to Kinesis stream
def encode_and_send_frame(frame, frame_count, enable_kinesis=True, enable_rekog=False, write_file=False):
    try:
        #convert opencv Mat to jpg image
        #print "----FRAME---"
        retval, buff = cv2.imencode(".jpg", frame)

        img_bytes = bytearray(buff)

        utc_dt = pytz.utc.localize(datetime.datetime.now())
        now_ts_utc = (utc_dt - datetime.datetime(1970, 1, 1, tzinfo=pytz.utc)).total_seconds()

        frame_package = {
            'ApproximateCaptureTime' : now_ts_utc,
        'FrameCount' : frame_count,
            'ImageBytes' : img_bytes
        }

        if write_file:
            print("Writing file img_{}.jpg".format(frame_count))
            target = open("img_{}.jpg".format(frame_count), 'w')
            target.write(img_bytes)
            target.close()

        #put encoded image in kinesis stream
        if enable_kinesis:
            print "Sending image to Kinesis"
            response = kinesis_client.put_record(
                StreamName="FrameStream",
                Data=cPickle.dumps(frame_package),
                PartitionKey="partitionkey"
            )
            print response

        if enable_rekog:
            response = rekog_client.detect_labels(
                Image={
                    'Bytes': img_bytes
                },
                MaxLabels=rekog_max_labels,
                MinConfidence=rekog_min_conf
            )
            print response

    except Exception as e:
        print e


def main():
    global commandFlag
    #capture_rate   
    argv_len = len(sys.argv)

    if argv_len > 1 and sys.argv[1].isdigit():
        capture_rate = int(sys.argv[1])

    cap = cv2.VideoCapture(0) #Use 0 for built-in camera. Use 1, 2, etc. for attached cameras.
    pool = Pool(processes=3)

    frame_count = 0
    while True:
        # Capture frame-by-frame
        ret, frame = cap.read()
        #cv2.resize(frame, (640, 360));

        if ret is False:
            break

        if frame_count % 30 == 0:
        result = pool.apply_async(encode_and_send_frame, (frame, frame_count, True, False, False,))

        frame_count += 1

        # Display the resulting frame
        cv2.imshow('frame', frame)

        #if cv2.waitKey(1) & 0xFF == ord('q'):
        if commandFlag == 1:
          break;

    # When everything done, release the capture
    cap.release()
    cv2.destroyAllWindows()
    return


if __name__ == '__main__':

    t1 = multiprocessing.Process(target=main)
    t1.start()
    t2 = multiprocessing.Process(target=subscriber)
    t2.start()

    while True:
        if commandFlag == 1:
           t1.terminate()
           t2.terminate()
           sys.exit(1)

---

尝试将线程设置为

daemon

，您可以使用

t1.daemon=True

和

t2.daemon=True

，这样程序结束后线程将结束。@Axois:感谢您的响应！我以前试过。但我可能设置不正确。因此，让我问你——我应该在哪里设置这两个设置？我需要在程序中进行任何其他更改才能正常运行吗？

t1=threading.Thread（target=main，daemon=True）

t2=threading.Thread（target=subscriber，daemon=True）

您也不必调用

t1.join（）

和

t2.join（）

因为一旦脚本结束，线程就会结束。@Axis:当我使用

t1=threading.Thread（target=main，daemon=True）

语法时，我得到了错误

TypeError:\uu init（）\uuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuu？IIRC此命令仅适用于python的更高版本。如果您使用的是早期版本，您可以使用
t1.daemon=True
进行设置，但这对您有效吗？尝试将线程设置为
daemon
，您可以使用
t1.daemon=True
和
t2.daemon=True
进行设置，这样程序结束后线程将结束。@Axois：感谢您的响应！我以前试过。但我可能设置不正确。因此，让我问你——我应该在哪里设置这两个设置？我需要在程序中进行任何其他更改才能正常运行吗？
t1=threading.Thread（target=main，daemon=True）
t2=threading.Thread（target=subscriber，daemon=True）
您也不必调用
t1.join（）
和
t2.join（）
因为一旦脚本结束，线程就会结束。@Axis:当我使用
t1=threading.Thread（target=main，daemon=True）
语法时，我得到了错误
TypeError:\uu init（）\uuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuu？IIRC此命令仅适用于python的更高版本。如果您使用的是早期版本，可以通过使用
t1.daemon=True
进行设置，但这对您有用吗？