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Home/ Questions/Q 8079571
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Editorial Team
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Editorial Team
Asked: June 5, 20262026-06-05T16:08:54+00:00 2026-06-05T16:08:54+00:00

I’m trying to update my code to use cv2.SURF() as opposed to cv2.FeatureDetector_create(SURF) and

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I’m trying to update my code to use cv2.SURF() as opposed to cv2.FeatureDetector_create("SURF") and cv2.DescriptorExtractor_create("SURF"). However I’m having trouble getting the descriptors after detecting the keypoints. What’s the correct way to call SURF.detect?

I tried following the OpenCV documentation, but I’m a little confused. This is what it says in the documentation.

Python: cv2.SURF.detect(img, mask) → keypoints¶
Python: cv2.SURF.detect(img, mask[, descriptors[, useProvidedKeypoints]]) → keypoints, descriptors

How do I pass the keypoints in when making the second call to SURF.detect?

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  1. Editorial Team
    Editorial Team
    2026-06-05T16:08:56+00:00Added an answer on June 5, 2026 at 4:08 pm

    I am not sure whether i understand your questions correctly. But if you are looking for a sample of matching SURF keypoints, a very simple and basic one is below, which is similar to template matching:

    import cv2
    import numpy as np
    
    # Load the images
    img =cv2.imread('messi4.jpg')
    
    # Convert them to grayscale
    imgg =cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    
    # SURF extraction
    surf = cv2.SURF()
    kp, descritors = surf.detect(imgg,None,useProvidedKeypoints = False)
    
    # Setting up samples and responses for kNN
    samples = np.array(descritors)
    responses = np.arange(len(kp),dtype = np.float32)
    
    # kNN training
    knn = cv2.KNearest()
    knn.train(samples,responses)
    
    # Now loading a template image and searching for similar keypoints
    template = cv2.imread('template.jpg')
    templateg= cv2.cvtColor(template,cv2.COLOR_BGR2GRAY)
    keys,desc = surf.detect(templateg,None,useProvidedKeypoints = False)
    
    for h,des in enumerate(desc):
        des = np.array(des,np.float32).reshape((1,128))
        retval, results, neigh_resp, dists = knn.find_nearest(des,1)
        res,dist =  int(results[0][0]),dists[0][0]
    
        if dist<0.1: # draw matched keypoints in red color
            color = (0,0,255)
        else:  # draw unmatched in blue color
            print dist
            color = (255,0,0)
    
        #Draw matched key points on original image
        x,y = kp[res].pt
        center = (int(x),int(y))
        cv2.circle(img,center,2,color,-1)
    
        #Draw matched key points on template image
        x,y = keys[h].pt
        center = (int(x),int(y))
        cv2.circle(template,center,2,color,-1)
    
    cv2.imshow('img',img)
    cv2.imshow('tm',template)
    cv2.waitKey(0)
    cv2.destroyAllWindows()
    

    Below are the results I got (copy pasted template image on original image using paint):

    enter image description here

    enter image description here

    As you can see, there are some small mistakes. But for a startup, hope it is OK.

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