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#include "test_precomp.hpp"

using namespace std;
using namespace cv;

class CV_AgastTest : public cvtest::BaseTest
{
public:
    CV_AgastTest();
    ~CV_AgastTest();
protected:
    void run(int);
};

CV_AgastTest::CV_AgastTest() {}
CV_AgastTest::~CV_AgastTest() {}

void CV_AgastTest::run( int )
{
  for(int type=0; type <= 2; ++type) {
    Mat image1 = imread(string(ts->get_data_path()) + "inpaint/orig.png");
    Mat image2 = imread(string(ts->get_data_path()) + "cameracalibration/chess9.png");
    string xml = string(ts->get_data_path()) + format("agast/result%d.xml", type);

    if (image1.empty() || image2.empty())
    {
        ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA );
        return;
    }

    Mat gray1, gray2;
    cvtColor(image1, gray1, COLOR_BGR2GRAY);
    cvtColor(image2, gray2, COLOR_BGR2GRAY);

    vector<KeyPoint> keypoints1;
    vector<KeyPoint> keypoints2;
    AGAST(gray1, keypoints1, 30, true, type);
    AGAST(gray2, keypoints2, (type > 0 ? 30 : 20), true, type);

    for(size_t i = 0; i < keypoints1.size(); ++i)
    {
        const KeyPoint& kp = keypoints1[i];
        cv::circle(image1, kp.pt, cvRound(kp.size/2), Scalar(255, 0, 0));
    }

    for(size_t i = 0; i < keypoints2.size(); ++i)
    {
        const KeyPoint& kp = keypoints2[i];
        cv::circle(image2, kp.pt, cvRound(kp.size/2), Scalar(255, 0, 0));
    }

    Mat kps1(1, (int)(keypoints1.size() * sizeof(KeyPoint)), CV_8U, &keypoints1[0]);
    Mat kps2(1, (int)(keypoints2.size() * sizeof(KeyPoint)), CV_8U, &keypoints2[0]);

    FileStorage fs(xml, FileStorage::READ);
    if (!fs.isOpened())
    {
        fs.open(xml, FileStorage::WRITE);
        if (!fs.isOpened())
        {
            ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
            return;
        }
        fs << "exp_kps1" << kps1;
        fs << "exp_kps2" << kps2;
        fs.release();
        fs.open(xml, FileStorage::READ);
        if (!fs.isOpened())
        {
            ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
            return;
        }
    }

    Mat exp_kps1, exp_kps2;
    read( fs["exp_kps1"], exp_kps1, Mat() );
    read( fs["exp_kps2"], exp_kps2, Mat() );
    fs.release();

     if ( exp_kps1.size != kps1.size || 0 != cvtest::norm(exp_kps1, kps1, NORM_L2) ||
          exp_kps2.size != kps2.size || 0 != cvtest::norm(exp_kps2, kps2, NORM_L2))
    {
        ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
        return;
    }

    /*cv::namedWindow("Img1"); cv::imshow("Img1", image1);
    cv::namedWindow("Img2"); cv::imshow("Img2", image2);
    cv::waitKey(0);*/
  }

  ts->set_failed_test_info(cvtest::TS::OK);
}

TEST(Features2d_AGAST, regression) { CV_AgastTest test; test.safe_run(); }