混合编程之多线程

前言: 小白一个, 没有系统性的学习过python网络通信,只是单纯的cv加修改代码,仅作留念以及参考用,感谢互联网博主们和bito插件,使得chatGPT得以免费使用.
另外该多线程传输图片的速度比没有多线程执行还满,后续不对python服务端做优化,而改为C++服务端实现.写出来继续再分享把

前篇博客地址

python客户端

采用生存者消费者模式、模式２和joinablequeue库.
客户端实现还是比较简单的,麻烦在server端

import pickle
import time
from multiprocessing import Process, JoinableQueue
from queue import Queue

from multiprocessing.connection import Client, Listener

from client_apart import draw_box
from image import plot_boxes, img_encode
import os
from natsort import ns, natsorted

host = 'localhost'
port = 9006
total_time = 0


def img_product(img_queue, path, path_mode='image'):
    if path_mode == 'image':
        img = img_encode(path)
        img_obj = {
   
   'frame_num': 1, 'image': img}  # need frame_num?
        img_queue.put(img_obj)
    elif path_mode == 'dir':
        dir_list = os.listdir(path)
        files = natsorted(dir_list, alg=ns.PATH)  # 顺序读取文件名
        i = 1
        for filename in files:
            img_path = path + '/' + filename
            img = img_encode(img_path)
            img_obj = {
   
   'frame_num': i, 'image': img}  # need frame_num?
            i += 1
            img_queue.put(img_obj)
        img_queue.put({
   
   'frame_num': 0, 'image': "end"})  # end signal 
    img_queue.join()


def server_consumer(img_queue):
    # 1. send data
    while True:
        img_obj = img_queue.get()
        if img_obj is None:
            client.close()  # avoid connection-reset-by-peer
            break  # exit end
        data_bytes = pickle.dumps(img_obj)
        start = int(round(time.time() * 1000))
        start_time = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
        client.send(data_bytes)  # 40ms/per send img
        # print('send cost time: ', (end - start))
        img_queue.task_done()
        try:
            det_result = client.recv()
            end = int(round(time.time() * 1000))
            end_time = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
            print('recv cost time: ', (end-start))
        except EOFError:
            break
        det_result = pickle.loads(det_result)
        draw_box(det_result, img_obj)


if __name__ == '__main__':
    client = Client((host, port))
    Listener()
    img_dir = './data'
    one_img = './data/Enterprise001.jpg'
    mode = 'dir'

    img_jq = JoinableQueue()
    producer = Process(target=img_product, args=(img_jq, img_dir, mode,))
    consumer = Process(target=server_consumer, args=(img_jq,))
    consumer.daemon = True  # set daemon but not set join()

    producer.start()
    consumer.start()

    producer.join()

Python服务端

此处接受图片和发送结果线程处在一个类内,使得可以共享一个Listener,来自chatGPT的idea.

from ctypes import *
import ctypes
import time
impo