how to use SIFT in opencv

Question

I am learning C++ and OpenCV these days. Given an image, I want to extract its SIFT features. From http://docs.opencv.org/modules/nonfree/doc/feature_detection.html, we can know

Answer 1

I was having the same question for opencv3 but i found this. It explains why SIFT and SURF removed from the default install of OpenCV 3.0 and how to use SIFT and SURF in OpenCV 3.

The algorithms and associated implementations in opencv_contrib are not installed by default and you need to explicitly enable them when compiling and installing OpenCV to obtain access to them.

They are move to xfeatures2d library.
#include <opencv2/xfeatures2d.hpp>

Answer 2

Update for OpenCV 4.2.0 (don’t forget to link opencv_xfeatures2d420.lib, of course)

#include <opencv2/core.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/xfeatures2d.hpp>

int main(int argc, char** argv)
{
    const cv::Mat input = cv::imread("input.jpg", 0); //Load as grayscale

    cv::Ptr<cv::xfeatures2d::SIFT> siftPtr = cv::xfeatures2d::SIFT::create();
    std::vector<cv::KeyPoint> keypoints;
    siftPtr->detect(input, keypoints);

    // Add results to image and save.
    cv::Mat output;
    cv::drawKeypoints(input, keypoints, output);
    cv::imwrite("sift_result.jpg", output);it.

    return 0;
}

Answer 3

See the example from Sift implementation with OpenCV 2.2

#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/nonfree/features2d.hpp> //Thanks to Alessandro

int main(int argc, const char* argv[])
{
    const cv::Mat input = cv::imread("input.jpg", 0); //Load as grayscale

    cv::SiftFeatureDetector detector;
    std::vector<cv::KeyPoint> keypoints;
    detector.detect(input, keypoints);

    // Add results to image and save.
    cv::Mat output;
    cv::drawKeypoints(input, keypoints, output);
    cv::imwrite("sift_result.jpg", output);

    return 0;
}

Tested on OpenCV 2.4.8

Answer 4

update for OpenCV3

#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/nonfree/features2d.hpp> //Thanks to Alessandro

int main(int argc, const char* argv[])
{
    const cv::Mat input = cv::imread("input.jpg", 0); //Load as grayscale

    cv::Ptr<cv::SiftFeatureDetector> detector = cv::SiftFeatureDetector::create();
    std::vector<cv::KeyPoint> keypoints;
    detector->detect(input, keypoints);

    // Add results to image and save.
    cv::Mat output;
    cv::drawKeypoints(input, keypoints, output);
    cv::imwrite("sift_result.jpg", output);

    return 0;
}