Open Source Computer Vision Library https://opencv.org/
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/*M///////////////////////////////////////////////////////////////////////////////////////
//
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// If you do not agree to this license, do not download, install,
// copy or use the software.
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//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
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#include "test_precomp.hpp"
using namespace std;
using namespace cv;
class CV_FastTest : public cvtest::BaseTest
{
public:
CV_FastTest();
~CV_FastTest();
protected:
void run(int);
};
CV_FastTest::CV_FastTest() {}
CV_FastTest::~CV_FastTest() {}
void CV_FastTest::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("fast/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;
FAST(gray1, keypoints1, 30, true, type);
FAST(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 != norm(exp_kps1, kps1, NORM_L2) ||
exp_kps2.size != kps2.size || 0 != 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_FAST, regression) { CV_FastTest test; test.safe_run(); }