[Python] python multiprocess problem with OpenCV returning key points

I'm using multiprocess Python module to parallelise processing with OpenCV algorithms (e.g. ORB detector/descriptor). The multiprocess module works fine in most cases, but when it comes to returning a list of cv2.KeyPoint objects there is a problem - all fields of each key point are set to 0 when returned to the caller process, although inside the worker process all key points are correct (as returned by OpenCV).

Here is minimal example that can be used to reproduce the error (you will need an image file called lena.png to make it work):

import numpy as np

from cv2 import ORB_create, imread, cvtColor, COLOR_BGR2GRAY
from multiprocess import Pool

feature = ORB_create(nfeatures=4)

def proc(img):
return feature.detect(img)

def good(feat, frames):
return map(proc, frames)

def bad(feat, frames):
# this starts a worker process
# and then collects result
# but something is lost on the way
pool = Pool(4)
return pool.map(proc, frames)

if __name__ == '__main__':
# it doesn't matter how many images
# a list of images is required to make use of
# pool from multiprocess module
rgb_images = map(lambda fn: imread(fn), ['lena.png'])
grey_images = map(lambda img: cvtColor(img, COLOR_BGR2GRAY), rgb_images)
good_kp = good(feature, grey_images)
bad_kp = bad(feature, grey_images)

# this will fail because elements in
# bad_kp will all contain zeros
for i in range(len(grey_images)):
for x, y in zip(good_kp, bad_kp):
# these should be the same
print('good: pt=%s angle=%s size=%s - bad: pt=%s angle=%s size=%s' % (x.pt, x.angle, x.size, y.pt, y.angle, y.size))
assert x.pt == y.pt


Platforms: both CentOS 7.6 and Windows 10 x64

Versions:

• 
  Python version: 2.7.15
  
  
• 
  multiprocess: 0.70.6.1
  
  
• 
  opencv-python-headless: 3.4.5.20 and 4.0.0.21
  

Is there a way to work around this? Use of standard multiprocessing module is not an option because of heavy usage of lambdas and callable objects which "can't be pickled".

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