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我有一个 python 函数,它接受图像路径并根据图像是否为黑色输出真或假。我想在同一台机器上处理多个图像,如果其中一个不是黑色的,则停止该过程。我在这里阅读了很多关于 python、celery 等的多处理,但我不知道从哪里开始。

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2 回答 2

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我建议查看Pools以轻松地动态创建进程。如果您需要一些共享状态,在这种情况下,已找到指示非黑色图像的布尔值,请查看Managers

更新:这是我的意思的一个例子。

import multiprocessing.Manager as Manager
import multiprocessing.Pool as Pool

m = Manager()
p = Pool(processes=5)

state_info = m.dict()
state_info['image_found'] = False

def processImage(img):

    # ... Process Image ...

    if imageIsBlack(img):
        state_info['image_found'] = True
        p.terminate()

 p.apply(processImage, imageList)

 if state_info['image_found']:
     print 'There was a black image!!'
 else:
     print 'No black images were found.'
于 2013-02-08T21:59:46.547 回答
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最后,这对我很有效。从此处的示例中复制它。出于说明目的,我已将我的 _isImgNonBlack 函数和图像序列替换为 0 和 1 的列表,其中 0 是黑色图像,1 个非黑色图像。

import multiprocessing

def isImgNonBlack(result_queue, imgSeq):
    for img in imgSeq:
        # If a non-black is found put a result
        if img==1:
            result_queue.put(1)

    # else put a zero as the result
    result_queue.put(0)

if __name__ == '__main__':
    processs = []
    result_queue = multiprocessing.Queue()
    nbProc = 20

    # making a fake list of images with 
    # 10,000 0's follwed by a single 1
    images = [0 for n in range(10000)]
    images.append(1)

    for n in range(nbProc): # start processes crawling for the result
        process = multiprocessing.Process(target=isImgNonBlack, args=[result_queue, images])
        process.start()
        processs.append(process)
        print 'Starting Process : %s' % process

    result = result_queue.get() # waits until any of the proccess have `.put()` a result

    for process in processs: # then kill them all off
        process.terminate()

    # finally print the result
    print "Seq have a non black img: %s" % result
于 2013-02-12T16:24:42.060 回答