Using numpy array for feature detection

Python
,
1

I am trying to use OpenCVs feature detection on numpy arrays. Unfortunately OpenCV raises an error when I want to detect features:

error: OpenCV(4.0.1) C:\ci\opencv-suite_1573470242804\work\modules\imgproc\src\resize.cpp:3787: error: (-215:Assertion failed) inv_scale_x > 0 in function 'cv::resize'

I tried it in the context of a bigger project but my minimum working example is:

import cv2 as cv
import numpy as np
from numpy import random
import matplotlib.pyplot as plt

orb_parameters = dict(nfeatures=15000,scaleFactor=1.2,nlevels=30,firstLevel=0,WTA_K=2,scoreType=1,patchSize=20,fastThreshold=2)

descriptor = cv.ORB_create(**orb_parameters)
detector = descriptor

FLANN_INDEX_LSH = 6
index_params = dict(algorithm=FLANN_INDEX_LSH,table_nummer=6,key_size=12,multi_probe_level=1)
search_params = dict(checks = 50)

matcher = cv.FlannBasedMatcher(index_params,search_params)

np_scene = random.randint(0,255,(80,80),np.uint8)
np_query = random.randint(0,255,(80,80),np.uint8)

keypoints_query = detector.detect(np_query,None)
keypoints_scene = detector.detect(np_scene,None)

keypoints_query, descriptors_query = descriptor.compute(np_query, keypoints_query)
keypoints_scene, descriptors_scene = descriptor.compute(np_scene, keypoints_scene)

matches = matcher.knnMatch(descriptors_query,descriptors_scene,k=2)

drawnMatches = cv.drawMatches(np_query, keypoints_query, np_scene, keypoints_scene, matches)

plt.figure()
plt.imshow(drawnMatches)
plt.show()

Could somebody point me in the right direction on how to use the feature detection functionality of OpenCV with numpy arrays?

2

welcome.

have you given your parameters much thought? please vary the parameters of your ORB instances.

30 levels of factor 1.2 gives you a factor of 237. I believe your parameters are nonsensical for the size of input (80x80) you give. and so is asking for fifteen thousand features from a noisy patch of 80x80.

3

Thank you crackwitz, you are right. The size of my input array is not sufficient for my ORB settings. I got these parameters with a bigger array and thought it would apply for a smaller one. From cv::ORB Class Reference I thought the fifteen thousand features are equal to a maximum feature count (0 to 15k features) which ORB would detekt and in my preliminary testing this worked fine:
grafik

Unfortunately, these arrays expend in the runtime and at the start they are obviously too small and therefore producing the error.

Is there a guideline in regards to the tuning of parameters?

4

not really, apart from trial and error and experience. I suppose it might help to read the original paper on ORB but I didn’t.

granted, OpenCV code could be more helpful in its error message… that seems to happen during the algorithm’s operation. it should sanity check its inputs some more.

1 Like
5

Well, yes in this situation I would have expected a more meaningful tracelog or even the feature detector not replying at all till it has enought size to operate.

I have read the paper, but it seems I have to read it again more thouroughly to tune my parameters.

However, thank you that answers my question :slight_smile: