What is the correct way to call this OpenCV function from Python?

I would like to use the selective search algorithm to segment images into possible object locations. I found that the library I already use for computer vision, OpenCV, implements this functionality as shown in the documentation here. However, I'm using Python and not C++, so I looked through OpenCV's github repositories until I found the example that I reproduced below.

#!/usr/bin/env python

'''
A program demonstrating the use and capabilities of a particular image segmentation algorithm described
in Jasper R. R. Uijlings, Koen E. A. van de Sande, Theo Gevers, Arnold W. M. Smeulders:
    "Selective Search for Object Recognition"
International Journal of Computer Vision, Volume 104 (2), page 154-171, 2013
Usage:
    ./selectivesearchsegmentation_demo.py input_image (single|fast|quality)
Use "a" to display less rects, 'd' to display more rects, "q" to quit.
'''

import cv2
import sys

if __name__ == '__main__':
    img = cv2.imread(sys.argv[1])

    cv2.setUseOptimized(True)
    cv2.setNumThreads(8)

    gs = cv2.ximgproc.segmentation.createSelectiveSearchSegmentation()
    gs.setBaseImage(img)

    if (sys.argv[2][0] == 's'):
        gs.switchToSingleStrategy()

    elif (sys.argv[2][0] == 'f'):
        gs.switchToSelectiveSearchFast()

    elif (sys.argv[2][0] == 'q'):
        gs.switchToSelectiveSearchQuality()
    else:
        print(__doc__)
        sys.exit(1)

    rects = gs.process()
    nb_rects = 10

    while True:
        wimg = img.copy()

        for i in range(len(rects)):
            if (i < nb_rects):
                x, y, w, h = rects[i]
                cv2.rectangle(wimg, (x, y), (x+w, y+h), (0, 255, 0), 1, cv2.LINE_AA)

        cv2.imshow("Output", wimg);
        c = cv2.waitKey()

        if (c == 100):
            nb_rects += 10

        elif (c == 97 and nb_rects > 10):
            nb_rects -= 10

        elif (c == 113):
            break

    cv2.destroyAllWindows()

Unfortunately, running this program with the command python selective_search.py "/home/christopher/DroneKit/Vision/Face Detection/Annotated Faces in the Wild/originalPics/2002/07/19/big/img_135.jpg" f gives me the following error:

Traceback (most recent call last):
  File "selective_search.py", line 37, in <module>
    rects = gs.process()
TypeError: Required argument 'rects' (pos 1) not found

Based upon that error message, I figured maybe I could just pass it a Python list and then the underlying C++ function would fill it with the algorithm's output. However, when I excecuted the following code:

rects = []
gs.process(rects)
print(rects)

The output was an empty list, and the image was displayed with no rectangles drawn on it. Therefore, I am at a loss on how I should call gs.process(). If it helps, the C++ declaration of the function is

CV_WRAP virtual void process(CV_OUT std::vector<Rect>& rects) = 0;

(Edit) Additional information copied from the comments:

Output from help(gs.process):

process(...) method of cv2.ximgproc_segmentation_SelectiveSearchSegmentation instance process(rects) -> None. rects = gs.process(rects) just makes rects None and causes the program to terminate with an exception

Using rects = gs.process(rects) sets rects to None and causes the program to terminate with an exception.

OpenCV version is 3.2.0.

Using a numpy array instead of a python list crashes my program with the following message:

OpenCV Error: Assertion failed (channels() == CV_MAT_CN(dtype)) in copyTo, file /home/christopher/opencv/modules/core/src/copy.cpp, line 259
terminate called after throwing an instance of 'cv::Exception'
  what():  /home/christopher/opencv/modules/core/src/copy.cpp:259: error: (-215) channels() == CV_MAT_CN(dtype) in function copyTo

Aborted (core dumped)