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Very similar pictures, but descriptors vary greatly Image: https://drive.google.com/open?id=1NAfI_h4QxM9vDMCH_gXogWbwQC_

Very similar pictures, but descriptors vary greatly Image: https://drive.google.com/open?id=1NAfI_h4QxM9vDMCH_gXogWbwQC_

Very similar pictures, but descriptors vary greatly Image: https://drive.google.com/open?id=1NAfI_h4QxM9vDMCH_gXogWbwQC_

Very similar pictures, but descriptors vary greatly Image: https://drive.google.com/open?id=1NAfI_h4QxM9vDMCH_gXogWbwQC_

github release : https://github.com/opencv/opencv/releases

thank you !

output error:

  terminate called after throwing an instance of 'cvflann::anyimpl::bad_any_cast'

My code:

cvflann::Matrix<uchar> data((uchar*) fetaures.data, fetaures.rows,
        fetaures.cols);
cvflann::Index<cvflann::Hamming<uchar>> flann_index(data,
        cvflann::LshIndexParams(10, 10, 10));
flann_index.buildIndex();

Ptr<ORB> detector = ORB::create(minHessian);
std::vector<cv::KeyPoint> keypoints;
cv::Mat queryDescriptors;
detector->detectAndCompute(Q, noArray(), keypoints, queryDescriptors);

Mat disMat(cv::Size(queryDescriptors.rows, queryDescriptors.cols), CV_32F);
Mat indeicesMat(cv::Size(queryDescriptors.rows, queryDescriptors.cols),
        CV_32F);
cvflann::Matrix<unsigned char> queries((unsigned char*) queryDescriptors.data,
        queryDescriptors.rows, queryDescriptors.cols);
cvflann::Matrix<int> indices((int*) indeicesMat.data, queryDescriptors.rows,
        queryDescriptors.cols);
cvflann::Matrix<int> dists((int*) disMat.data, queryDescriptors.rows,
        queryDescriptors.cols);
flann_index.knnSearch(queries, indices, dists, knn,
        cvflann::SearchParams(32));

And I found cvflann:index and cv::flann::index, which should i use?

use knnSearch, terminate called after throwing an instance of 'cvflann::anyimpl::bad_any_cast' output error: terminat

for (int i = 1; i < descriptors.size(); i++) { cv::vconcat(samples_32f, descriptors.at(i), samples_32f);

samples_32f is a descriptor for many pictures

to search image lable

cv::flann::Index flann_index(samples_32f, cv::flann::LshIndexParams(10, 10, 10)); can work.

use knnSearch, terminate called after throwing an instance of 'cvflann::anyimpl::bad_any_cast' output error: terminat

https://answers.opencv.org/question/10358/how-to-match-orb-descriptors-with-flann-lsh/ i see that post. but the method

i found on document that only some Machine Learning support ouput the distance to the margin

use knnSearch, terminate called after throwing an instance of 'cvflann::anyimpl::bad_any_cast' output error: terminat

A picture is a class, and I want to combine it with the recognition of AR. thank you!

witch Machine Learning i shoud use? I have 200 images and 200 classes and I try to use opencv cv :: ml :: Boost cv :: ml

witch Machine Learning i shoud use? I have 200 images and 200 classes and I try to use opencv cv :: ml :: Boost cv :: ml

Error message: terminate called after throwing an instance of 'cv::Exception'

what(): OpenCV(4.1.2-dev) /home/ztftrue/Downloads/opencv/modules/features2d/src/matchers.cpp:756: error: (-215:Assertion failed) _queryDescriptors.type() == trainDescType in function 'knnMatchImpl'

Code:

Mat input = cv::imread("input.jpg",IMREAD_COLOR);
cout << "input type: "<<input.type() << endl;
cout << "descriptors type: " << descriptors.type() << endl;
bowide.compute(input, keypoints, descriptors);

Out put:

input type: 21 descriptors type: 0

I try:

input.convertTo(input, CV_32F, 1 / 255.0);

or

input.convertTo(input, CV_32F);

and filter keypoint vector

      if (!keypoints.empty() && keypoints.size() > 10) {
            cv::Mat descriptors;
        extractor->compute(it, keypoints, descriptors);
        if (!descriptors.empty()) {
            descriptors.convertTo(descriptors, CV_32F);
            trainingDescriptors.push_back(descriptors);
        } else {
            std::cout << "- No descriptors found." << std::endl;
            }
    } else {
        std::cout << "- No keypoints found." << std::endl;
    }

thank you very much , i searched it https://answers.opencv.org/question/93682/svm-model-fails-to-load/ , now it work.

SVM predict error error: (-215:Assertion failed) samples.cols == var_count && samples.type() == CV_32F in func

CMake Error: CMake was unable to find a build program corresponding to "Unix Makefiles". CMAKE_MAKE_PROGRAM is not set.

I don't know which method should be used to achieve my goal. I have multiple pictures and multiple tags. Because tags ha

How to use DescriptorMatcher to get matching images? I have some images, and I want to use DescriptorMatcher to get matc

I want to know which image the matcher matched

thank you , i update my question

How to use DescriptorMatcher to get matching images? I have some images, and I want to use DescriptorMatcher to get matc

How to use DescriptorMatcher to get matching images? I have some images, and I want to use DescriptorMatcher to get matc

issue : https://github.com/opencv/opencv/issues/15984

System information (version) OpenCV => 4.1.2-dev Operating System / Platform => ArchLinux 5.3.11-arch1-1

System information (version) OpenCV => 4.1.2-dev Operating System / Platform => ArchLinux 5.3.11-arch1-1

SVM->trainAuto() Segmentation fault (core dumped) Code: outSVM = cv::ml::SVM::create(); outSVM->setType(SVM::C_SV

This doesn't work, I don't know where something went wrong.

How to get svm predict socres? image read: Mat image = imread(buffer, IMREAD_GRAYSCALE); predict: SVM->predict(im

How to get svm predict socres? image read: Mat image = imread(buffer, IMREAD_GRAYSCALE); predict: SVM->predict(im

issues: https://github.com/opencv/opencv_contrib/issues/2351

ArchLinux 5.3.9-1-default #1 SMP Thu Nov 7 07:06:36 UTC 2019 (b0d4923) x86_64 x86_64 x86_64 GNU/Linux

I have 16GB memory for this application