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Thank you for the clarifdication!

cv.detail.BestOf2NearestRangeMatcher_create(), used in stitching_detailed.py seems missing from OpenCv4.2.

Line 244++:

    if matcher_type == "affine":
        matcher = cv.detail_AffineBestOf2NearestMatcher(False, try_cuda, match_conf)
    elif range_width == -1:
        matcher = cv.detail.BestOf2NearestMatcher_create(try_cuda, match_conf)
    else:
        matcher = cv.detail.BestOf2NearestRangeMatcher_create(range_width, try_cuda, match_conf)
    return matcher 

Will this be added into a future version? Is there a current work-around?

Thanks?

Ln 34: cv.detail_BestOf2NearestRangeMatcher vs cv.detail**.**BestOf2NearestRangeMatcher**_create** cv.detail_BestOf2Nea

Ln 34: cv.detail_BestOf2NearestRangeMatcher vs cv.detail.BestOf2NearestRangeMatcher_create cv.detail_BestOf2NearestRang

Ln 34: cv.detail_BestOf2NearestRangeMatcher vs cv.detail.BestOf2NearestRangeMatcher_create

AttributeError: module 'cv2.detail' has no attribute 'BestOf2NearestRangeMatcher_create' Im refering to BestOf2NearestR

AttributeError: module 'cv2.detail' has no attribute 'BestOf2NearestRangeMatcher_create'

cv.detail.BestOf2NearestRangeMatcher_create() missing cv.detail.BestOf2NearestRangeMatcher_create(), used in stitching_d

If I understand correctly, you have to set your router to forward the port to the LAN-IP, and then exchange the LAN-IP w

Here is how I solved the issue: Essentially, if I replace src = src_bgr; with src_bgr.copyTo(src); or gpu_src.upload(s

Here is how I solved the issue: Essentially, if I replace src = src_bgr; with src_bgr.copyTo(src); or gpu_src.upload(s

CUDA::remap with shared-memory -> black output I am trying to undistort images by using CUDA following the 'aged' (op

Here is how I solved the issue: Essentially, if I replace src = src_bgr; with src_bgr.copyTo(src); or gpu_src.upload(s

Thanks for your reply! I want to use SHARED as it should be the fastest option, but the image I receive is black. So I w

Thanks for your reply! I want to use SHARED as it should be the fastest option, but the image I receive is black. So I w

Thanks for your reply! I want to use SHARED as it should be the fastest option, but the image I receive is black. So I w

CUDA::remap with shared-memory -> black output I am trying to undistort images by using CUDA following the 'aged' (op

CUDA::remap with shared-memory -> black output I am trying to undistort images by using CUDA following the 'aged' (op

CUDA::remap shared-memory I am trying to undistort images by using CUDA following the 'aged' (opencv2) approach from her

Thanks for your reply! I want to use SHARED as it should be the fastest option, but the image I receive is black. So I w

Thanks for your reply! if I change cv::cuda::HostMem cudamem_src(src_bgr.size(), CV_8UC3, cv::cuda::HostMem::Alloc

As far as I know SIFT is not available for CUDA. But you can try SURF or ORB ... Also note that SIFT and SURF are patent

CUDA::remap shared-memory I am trying to undistort images by using CUDA following the 'aged' (opencv2) approach from her

I have a little experience with OpenCV (Python) and just received a Jetson Nano and want to test OpenCV with CUDA. So I tried an ORB-example but am stuck with converting GPU-Keypoints to CPU-Keypoints, but I am unable to get any result.

def orb_with_cuda():
        MAX_FEATURES = 100
        GOOD_MATCH_PERCENT = 0.15
        # load images into numpy
        npMat1 = get_sample("im1.jpg")
        npMat2 = get_sample("im2.jpg")        
        # upload into Cuda
        cuMat1 = cv2.cuda_GpuMat()
        cuMat2 = cv2.cuda_GpuMat()
        cuMat1.upload(npMat1)
        cuMat2.upload(npMat2)        
        #convert to Gray
        cuMat1g = cv2.cuda.cvtColor(cuMat1, cv2.COLOR_RGB2GRAY)
        cuMat2g = cv2.cuda.cvtColor(cuMat2, cv2.COLOR_RGB2GRAY)

        #ORB
        corb = cv2.cuda_ORB.create(MAX_FEATURES)
        _kps1, _descs1 = corb.detectAndComputeAsync(cuMat1g, None)
        _kps2, _descs2 = corb.detectAndComputeAsync(cuMat2g, None)

        #convert Keypoints to CPU
        kps1 = [cv2.KeyPoint() for i in range(MAX_FEATURES)]
        kps2 = [cv2.KeyPoint() for i in range(MAX_FEATURES)]
        corb.convert(_kps1, kps1)
        corb.convert(_kps2, kps2)      

        #BruteForce Matching
        cbf = cv2.cuda_DescriptorMatcher.createBFMatcher(cv2.NORM_HAMMING)
        cmatches = cbf.match(_descs1, _descs2) 
        # Sort matches by score
        cmatches.sort(key=lambda x: x.distance, reverse=False)
        # Remove not so good matches
        numGoodMatches = int(len(cmatches) * GOOD_MATCH_PERCENT)
        cmatches = cmatches[:numGoodMatches]  
        # Draw top matches
        imMatches = cv2.drawMatches(npMat1, kps1, npMat2, kps2, cmatches, None)
        cv2.imwrite("gpu_matches.jpg", imMatches)
        return()

The code above is running w/o any errors, but it seems the CPU-keypoints are all empty (the created images does not show any matching lines). The equivalent Non-CUDA code is running fine.

Any idea what I am doing wrong? I tried several conversion methods, this is the 'best' I can find. Thanks for your help!

(Using OpenCV4.1.2 on Jetson Nano with Python3.6.9)

I re-compiled the .hpp and everything is working! Thank you so much for your help!

Sorry, did not know I have to recompile ... Do I have to recompile the entire OpenCV, or is there a faster way? (using L

Sorry, did not know I have to recompile ... Do I have to recompile the entire OpenCV, or is there a faster way?

Thanks, this seems to be working! I have to wait for a couple of hours before I can show the answer

Thanks, this seems to be working! I have to wait for a couple of hours before I can show show the answer

Thanks for your help! Too bad the solution is not working: The line imMatches = cv2.drawMatches(npMat1, corb.convert(_

@supra56: using cuMat1 = cv2.cuda_GpuMat() cuMat2 = cv2.cuda_GpuMat() cuMat1g = cv2.cvtColor(npMat1, cv2.COLOR_RGB2GR

cmatches is <class 'list'=""> of <class 'cv2.dmatch'="">. You, are right I did some nonsense in my earlier

@cudawarped: Thanks for your help! _kps1.download() shows a <class 'numpy.ndarray'=""> with [[2.54100000e+03 4.

@supra56: Thanks for your help! I changed the lines to cuMat1 = cv2.cuda_GpuMat() cuMat2 = cv2.cuda_GpuMat()

Cuda ORB keypoints I have a little experience with OpenCV (Python) and just received a Jetson Nano and want to test Open