无法腌制<类型'cv2.BRISK'&gt ;:属性查找cv2.BRISK失败 [英] Can't pickle <type 'cv2.BRISK'>: attribute lookup cv2.BRISK failed

问题描述

我正在尝试同时运行多个 CMT跟踪器.因此，我设置了一个线程池:

I'm trying to run multiple CMT trackers simultaneously. For that reason, I'm setting a Pool of threads:

import argparse
import cv2
from multiprocessing import Pool
import numpy as np
import os
import sys
import time

import VARtracker
import util

CMT1 = VARtracker.CMT()

... # code lines removed

# Clean up
cv2.destroyAllWindows()

if args.inputpath is not None:
    # If a path to a file was given, assume it is a single video file
    if os.path.isfile(args.inputpath):
        cap = cv2.VideoCapture(args.inputpath)
        # Skip first frames if required
        if args.skip is not None:
            cap.set(cv2.cv.CV_CAP_PROP_POS_FRAMES, args.skip)

    # Otherwise assume it is a format string for reading images
    else:
        cap = util.FileVideoCapture(args.inputpath)
        # Skip first frames if required
        if args.skip is not None:
            cap.frame = 1 + args.skip

    # Check if videocapture is working
    if not cap.isOpened():
        print 'Unable to open video input.'
        sys.exit(1)

    # Read first frame
    status, im0 = cap.read()
    im_gray0 = cv2.cvtColor(im0, cv2.COLOR_BGR2GRAY)
    im_draw = np.copy(im0)

# Getting initial bounding boxes
tl1 = [405, 160]
br1 = [450, 275]

VARtracker.initialise(CMT1, im_gray0, tl1, br1)

frame = 1
while True:
    pool = Pool(processes=4)
    print frame

    # Read image
    status, im = cap.read()
    if not status:
        break
    im_gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
    im_draw = np.copy(im)

    tic = time.time()
    # Serial approach
    #res1 = VARtracker.process_frame(CMT1, im_gray)

    # Parallel approach
    res1 = pool.apply_async(VARtracker.process_frame, (CMT2, im_gray))
    pool.close()
    pool.join()
    res1 = res1.get()
    toc = time.time()

    # Display results
    if res1.has_result:
        cv2.line(im_draw, res1.tl, res1.tr, (255, 0, 0), 4)
        cv2.line(im_draw, res1.tr, res1.br, (255, 0, 0), 4)
        cv2.line(im_draw, res1.br, res1.bl, (255, 0, 0), 4)
        cv2.line(im_draw, res1.bl, res1.tl, (255, 0, 0), 4)

    if not args.quiet:
        cv2.imshow('main', im_draw)
        cv2.waitKey(pause_time)

    # Remember image
    im_prev = im_gray
    frame += 1

每当我评论串行方法并尝试使用线程(并行方式)时，都会遇到以下错误:

Whenever I comment the Serial approach and attempt using threads (Parallel aproach), I come across the following error:

回溯(最近通话最近一次):

Traceback (most recent call last):

res1 = res1.get()模块中的文件"/home/rafael/GIT/CMT-Tracker/VaretoCMT/VARmain.py"，第128行

File "/home/rafael/GIT/CMT-Tracker/VaretoCMT/VARmain.py", line 128, in module res1 = res1.get()

在文件"/usr/lib/python2.7/multiprocessing/pool.py"的第558行中，获取提高self._value值

File "/usr/lib/python2.7/multiprocessing/pool.py", line 558, in get raise self._value

cPickle.PicklingError:无法腌制:属性查找cv2.BRISK失败

cPickle.PicklingError: Can't pickle : attribute lookup cv2.BRISK failed

可以在 VARmain.py，VARtracker中遇到其他文件.py和util.py .

我已经尝试了很多方法，但仍然没有找到克服Python局限性的方法.我发现我不能序列化类方法，只能序列化函数.如果可能的话，我想使用Python标准库解决它.

I've tried so many ways and I still haven't found a way to overcome this Python limitation. I found out that I cannot serialize class methods, only functions. If possible, I would like to solve it using Python standard libraries.

推荐答案

我设法解决了这个问题.感谢@Matt和@Yamaneko. 基本上，我将读取图像的块移到了worker函数中.因此，如果 pool size = 6 并且有六个边界框，则每个帧将被读取六次(在每个工作程序中).这是我发现使其工作的唯一方法.

I managed to solve it. Thanks to @Matt and @Yamaneko. Basically, I moved the block that reads the image into the worker function. Therefore, if the pool size = 6 and there are six bounding boxes, each frame is going to be read six times (within each worker). That's the only way I have found to make it work.

当前版本可以在此处找到.

import cv2 as cv
import multiprocessing as mp
import time

def worker(folder_path, list_name, top_left, bot_right, index):
    frame_path = folder_path + '/' + list_name[0]
    image_0 = cv.imread(frame_path)
    gray_0 = cv.cvtColor(image_0, cv.COLOR_BGR2GRAY)

    cmt = VARtracker.CMT()
    cmt.initialise(gray_0, top_left, bot_right)
    box_queue = mp.Queue()

    for name in list_name:
        frame_path = folder_path + '/' + name
        image_now = cv.imread(frame_path)
        gray_now = cv.cvtColor(image_now, cv.COLOR_BGR2GRAY)

        cmt.process_frame(gray_now)
        if cmt.has_result:
            print index, name, zip(cmt.tl, cmt.br)
            output.put((index, name, zip(cmt.tl, cmt.br)))
    print 'Process {} finished'.format(index)

def VARmethod(folder_path, final_frame, top_left, bot_right):
    tic = time.time()

    if len(top_left) == len(bot_right):
        list_frame = [index for index in range(1, final_frame + 1)]
        list_name = [str(index) + '.jpg' for index in list_frame]

        pool = mp.Pool(5)
        for index in range(0, len(top_left)):
            pool.apply_async(worker, args=(folder_path, list_name, top_left[index], bot_right[index], index))
        pool.close()
        pool.join()

        print 'Finished with the script'

    toc = time.time()
    print output.qsize()
    print (toc - tic)

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