opencv/modules/features2d/test/test_fast.cpp
Hamdi Sahloul ef5579dc86 Merge pull request #12310 from cv3d:chunks/enum_interface
* Cleanup macros and enable expansion of `__VA_ARGS__` for Visual Studio

* Macros for enum-arguments backwards compatibility

* Convert struct Param to enum struct

* Enabled ParamType.type for enum types

* Enabled `cv.read` and `cv.write` for enum types

* Rename unnamed enum to AAKAZE.DescriptorType

* Rename unnamed enum to AccessFlag

* Rename unnamed enum to AgastFeatureDetector.DetectorType

* Convert struct DrawMatchesFlags to enum struct

* Rename unnamed enum to FastFeatureDetector.DetectorType

* Rename unnamed enum to Formatter.FormatType

* Rename unnamed enum to HOGDescriptor.HistogramNormType

* Rename unnamed enum to DescriptorMatcher.MatcherType

* Rename unnamed enum to KAZE.DiffusivityType

* Rename unnamed enum to ORB.ScoreType

* Rename unnamed enum to UMatData.MemoryFlag

* Rename unnamed enum to _InputArray.KindFlag

* Rename unnamed enum to _OutputArray.DepthMask

* Convert normType enums to static const NormTypes

* Avoid conflicts with ElemType

* Rename unnamed enum to DescriptorStorageFormat
2018-09-21 18:12:35 +03:00

139 lines
4.9 KiB
C++

/*M///////////////////////////////////////////////////////////////////////////////////////
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#include "test_precomp.hpp"
namespace opencv_test { namespace {
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, static_cast<FastFeatureDetector::DetectorType>(type));
FAST(gray2, keypoints2, (type > 0 ? 30 : 20), true, static_cast<FastFeatureDetector::DetectorType>(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_FAST, regression) { CV_FastTest test; test.safe_run(); }
}} // namespace