Python多处理挂起加入

时间:2018-11-29 06:33:40

标签: python process parallel-processing multiprocessing

我正在读取一个视频文件,以便每20帧将第一帧存储在Input Queue中。一旦在“输入队列”中获得了所有必需的帧,然后我将运行多个进程以对这些帧执行一些操作,并将结果存储在输出队列中。 但是代码始终卡在连接中,我尝试了针对此类问题提出的不同解决方案,但似乎没有一个起作用。

import numpy as np
import cv2
import timeit
import face_recognition
from multiprocessing import Process, Queue, Pool
import multiprocessing
import os

s = timeit.default_timer()

def alternative_process_target_func(input_queue, output_queue):

    while not output_queue.full():
        frame_no, small_frame, face_loc = input_queue.get()
        print('Frame_no: ', frame_no, 'Process ID: ', os.getpid(), '----', multiprocessing.current_process())
        #canny_frame(frame_no, small_frame, face_loc)

        #I am just storing frame no for now but will perform something else later
        output_queue.put((frame_no, frame_no)) 

        if output_queue.full():
            print('Its Full ---------------------------------------------------------------------------------------')
        else:
            print('Not Full')

    print(timeit.default_timer() - s, ' seconds.')
    print('I m not reading anymore. . .', os.getpid())


def alternative_process(file_name):
    start = timeit.default_timer()
    cap = cv2.VideoCapture(file_name)
    frame_no = 1
    fps = cap.get(cv2.CAP_PROP_FPS)
    length = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
    print('Frames Per Second: ', fps)
    print('Total Number of frames: ', length)
    print('Duration of file: ', int(length / fps))
    processed_frames = 1
    not_processed = 1
    frames = []
    process_this_frame = True
    frame_no = 1
    Input_Queue = Queue()
    while (cap.isOpened()):
        ret, frame = cap.read()
        if not ret:
            print('Size of input Queue: ', Input_Queue.qsize())
            print('Total no of frames read: ', frame_no)
            end1 = timeit.default_timer()
            print('Time taken to fetch useful frames: ', end1 - start)
            threadn = cv2.getNumberOfCPUs()
            Output_Queue = Queue(maxsize=Input_Queue.qsize())
            process_list = []
            #quit = multiprocessing.Event()
            #foundit = multiprocessing.Event()

            for x in range((threadn - 1)):
                # print('Process No : ', x)
                p = Process(target=alternative_process_target_func, args=(Input_Queue, Output_Queue))#, quit, foundit
                #p.daemon = True
                p.start()
                process_list.append(p)
                #p.join()

            # for proc in process_list:
            #     print('---------------------------------------------------------------', proc.p)

            i = 1
            for proc in process_list:
                print('I am hanged here')
                proc.join()
                print('I am done')
                i += 1

            end = timeit.default_timer()
            print('Time taken by face verification: ', end - start)

            break

        if process_this_frame:
            print(frame_no)
            small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)
            rgb_small_frame = small_frame[:, :, ::-1]
            face_locations = face_recognition.face_locations(rgb_small_frame)
            # frames.append((rgb_small_frame, face_locations))
            Input_Queue.put((frame_no, rgb_small_frame, face_locations))
            frame_no += 1

        if processed_frames < 5:
            processed_frames += 1
            not_processed = 1

        else:
            if not_processed < 15:
                process_this_frame = False
                not_processed += 1
            else:

                processed_frames = 1
                process_this_frame = True
                print('-----------------------------------------------------------------------------------------------')

    cap.release()
    cv2.destroyAllWindows()

alternative_process('user_verification_2.avi')

1 个答案:

答案 0 :(得分:1)

正如Process.join上的文档所述,(或“阻止” )正是预期发生的事情:

  

阻塞调用线程,直到其join()方法为   被叫终止或直到可选超时发生。

join停止当前线程,直到目标进程完成。目标进程正在调用alternative_process_target_func,因此问题显然出在该函数中。它永远不会结束。可能有多个原因。

问题1

alternative_process_target_func一直运行到output_queue.full()。如果永远没装满怎么办?它永远不会结束?最好以其他方式确定终点,例如运行直到输入队列为空。

问题2

如果输入队列为空,

input_queue.get()将阻塞。正如documentation所说:

  

从队列中删除并返回一个项目。如果可选的args阻止为true,并且超时为None(默认值),则在必要时阻止,直到有可用项为止。

您正在运行多个进程,因此不要仅仅因为output_queue.full()不久前为False,并且输入大小与输出大小相同而导致输入中没有东西。同时,可能发生了很多事情。

您想要做的是:

try:
    input_queue.get(false)  # or input_queue.get_nowait()
except Empty:
    break  # stop when there is nothing more to read from the input

问题3

output_queue.put((frame_no, frame_no))将在输出中没有空间存储数据时阻塞。

同样,您假设输出中有空间,只是因为您刚才检查了output_queue.full(),并且输入大小等于输出大小。永远不要依靠这种东西。

您要执行与输入相同的操作:

try:
    output_queue.put((frame_no, frame_no), false)
    # or output_queue.put_nowait((frame_no, frame_no))
except Empty:
    # deal with this somehow, e.g.
    raise Exception("There is no room in the output queue to write to.")