[英]Running python multiprocess for Image processing
我有一个python函数,它接收图像路径并根据图像是否为黑色输出true或false。 我想在同一台计算机上处理多个图像,如果其中一个不是黑色,也要停止该过程。 我在这里阅读了很多关于python,celery等的多重处理的信息,但是我不确定从哪里开始。
我建议您查看Pools,以轻松地动态创建流程。 如果需要某种共享状态(在这种情况下为布尔值,表明已找到非黑色图像),请查看Managers 。
更新:这是我的意思的示例。
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.'
最后,这对我很好。 从此处的示例复制。 为了说明起见,我将_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,而1是非黑色图像。
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
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