cv2.BOWImgDescriptorExtractor works with SIFT but not with ORB

edit

Dear Community

I hope you can help me out with the following question. I trained a vocabulary using cv2.BOWKMeansTrainer. When I try to get the visual word for a descriptor, using cv2.BOWImgDescriptorExtractor, this works fine for SIFT but crashes for ORB.

Relevant Code for SIFT (WORING)

def get_visual_word_histogram_of_images(vocabulary):
sift = cv2.xfeatures2d.SIFT_create()
bow_ext = cv2.BOWImgDescriptorExtractor(sift, cv2.BFMatcher(cv2.NORM_L2))
bow_ext.setVocabulary(vocabulary)

bow_list = []

for filename in listdir(PATH_TO_IMAGES):
    path_to_image = "{}{}".format(PATH_TO_IMAGES, filename)
    image = cv2.imread(path_to_image, 0)
    kp, des = sift.detectAndCompute(image, None)
    histogram = bow_ext.compute(image, kp)[0]
    bow_list.append((histogram, path_to_image))

return bow_list

Relevant Code for ORB (CRASHING)

def get_visual_word_histogram_of_images(vocabulary):
orb = cv2.ORB_create()
bow_ext = cv2.BOWImgDescriptorExtractor(orb, cv2.BFMatcher(cv2.NORM_HAMMING))
# bow_ext = cv2.BOWImgDescriptorExtractor(orb, cv2.BFMatcher(cv2.NORM_L2))
bow_ext.setVocabulary(vocabulary)

bow_list = []

for filename in listdir(PATH_TO_IMAGES):
    path_to_image = "{}{}".format(PATH_TO_IMAGES, filename)
    image = cv2.imread(path_to_image, 1)
    kp, des = orb.detectAndCompute(image, None)
    histogram = bow_ext.compute(image, kp)[0]
    bow_list.append((histogram, path_to_image))

return bow_list

Error Message produced by the ORB Code:

/home/kama/bin/anaconda3/envs/genistat/bin/python /home/kama/genistat/visual_scene_fingerprint/experiments/orb_bow_similarity.py
OpenCV Error: Assertion failed (_queryDescriptors.type() == trainDescType) in knnMatchImpl, file /feedstock_root/build_artefacts/opencv_1506439690741/work/opencv-3.3.0/modules/features2d/src/matchers.cpp, line 744
Traceback (most recent call last):
  File "/home/kama/genistat/visual_scene_fingerprint/experiments/orb_bow_similarity.py", line 89, in <module>
    run()
  File "/home/kama/genistat/visual_scene_fingerprint/experiments/orb_bow_similarity.py", line 75, in run
    bow_list = get_visual_word_histogram_of_images(vocabulary)
  File "/home/kama/genistat/visual_scene_fingerprint/experiments/orb_bow_similarity.py", line 49, in get_visual_word_histogram_of_images
    histogram = bow_ext.compute(image, kp)[0]
cv2.error: /feedstock_root/build_artefacts/opencv_1506439690741/work/opencv-3.3.0/modules/features2d/src/matchers.cpp:744: error: (-215) _queryDescriptors.type() == trainDescType in function knnMatchImpl

Where line 49 is the histogram = bow_ext.compute(image, kp)[0] statement.

The error message indicates, that I used another descriptor type for training. Which I did not... See the following code for training:

def train_vocabulary():
    k_means_trainer = cv2.BOWKMeansTrainer(100)
    for filename in listdir(PATH_TO_IMAGES):
        path_to_image = "{}{}".format(PATH_TO_IMAGES, filename)
        img = cv2.imread(path_to_image, cv2.IMREAD_GRAYSCALE)
        orb = cv2.ORB_create()
        key_points, descriptors = orb.detectAndCompute(img, None)

        if len(key_points) <= 0:
            continue
        descriptors = np.float32(descriptors)

        k_means_trainer.add(descriptors)
    vocabulary = k_means_trainer.cluster()
    return vocabulary

Any Ideas?

Installation: OS: Ubuntu 16.04 Python: 3.6.2 opencv 3.3.0 opencv3 3.1.0