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How to implement K nearest neighbour

asked 2016-03-22 07:50:56 -0500

Nbb gravatar image

updated 2016-03-22 08:10:05 -0500


I am trying to use KNN but calling Im not sure how to initialize it. CvKNearest knn; does not work. It says CvKNearest is undefined. I followed this

Is there a documentation that teaches me how to initialize classes in opencv ? I did this

flann::Index flan;

Mat M = (Mat_<double>(3, 3) << 1, 1, 1, 2, 2, 2, 3, 3, 3);

Mat query = (Mat_<double>(1, 3) << 1, 1, 1);
Mat index, dist;

flan.knnSearch(query, index, dist, 2);

But how do I tell the function to search the K nearest neighbour of Mat query given M (the data) ? It is giving me an error also, OpenCV Error: Assertion failed (query.type() == type && indices.type() == CV_32S && dists.type() == dtype) Help thanks. OpenCV is too hard for me.

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It is the explanation for the Python interface but the main idea is identical. Click here for more info!

StevenPuttemans gravatar imageStevenPuttemans ( 2016-03-22 08:17:33 -0500 )edit

please clarify, if you want to do a classification (use ml::KNearest) or find the closest n neighbours (use flann::Index), then we can help you further.

berak gravatar imageberak ( 2016-03-22 09:07:17 -0500 )edit

Hello, I am trying to find both. Find the closest n neighbours then classify it. The input to knnSearch does not have the training data. I can only input the vector I want to query. What function can i use to find the closest n neighbours ?

Something like KNN(query, data, output)

Nbb gravatar imageNbb ( 2016-03-23 05:02:51 -0500 )edit

the flann::Index does not classify, the ml::KNearest only gives you nearest class labels (not data items)

again, choose ;) (then we can come up with an example)

berak gravatar imageberak ( 2016-03-23 05:24:59 -0500 )edit

Hello thanks. I guess I would want ml::KNearest. I have looked through the doc but I am still extremely lost. Given an a Mat trainingData and Mat labels and Mat input, how do I use those functions to find the KNN ? ml::Knearest does not take in training data as input

Nbb gravatar imageNbb ( 2016-03-23 05:39:13 -0500 )edit

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answered 2016-03-23 05:49:23 -0500

berak gravatar image

updated 2016-03-23 05:53:27 -0500

so, here's a KNearest example for opencv3:

#include <iostream>
using namespace std;

#include <opencv2\opencv.hpp>
using namespace cv;
using namespace cv::ml;

int main(int argc, char **argv)
    Mat train_data, train_labels;
    Mat test_data, test_labels;
    Mat digits = imread("samples/data/digits.png",0); // have a look at it !
    for (int r=0; r<50; r++) // 10 digits a 5 rows
        for (int c=0; c<100; c++)  // 100 digits per row
            Mat num = digits(Rect(c*20,r*20,20,20));
            if (c%2==0) // 50/50 split
                train_data.push_back(num.reshape(1,1)); // each digit goes on a single row
                train_labels.push_back(int(r/5));  // we need 1 (integer) label per feature row
    Ptr<ml::KNearest> knn = ml::KNearest::create();
    knn->train(train_data, ml::ROW_DATA, train_labels);

    for (int i=0; i<test_data.rows; i++)
        Mat res;
        // predict on majority of k(5) neighbours:
        knn->findNearest(test_data.row(i), 5, res, neighbours);
        int e =<int>(i);
        int p = (int)<float>(0);
        cerr << e << " : " << p << " " << neighbours << endl;
    return 0;
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Amazing thanks berak ! knn->train(train_data, ml::ROW_DATA, train_labels); so that was how you got the function to store the samples :) Thanks again

Nbb gravatar imageNbb ( 2016-03-23 09:08:25 -0500 )edit
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Asked: 2016-03-22 07:50:56 -0500

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Last updated: Mar 23 '16