88 lines
3.0 KiB
C++
88 lines
3.0 KiB
C++
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#include "test_precomp.hpp"
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using namespace cv;
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using namespace std;
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class CV_HomographyTest: public cvtest::BaseTest
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{
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public:
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CV_HomographyTest();
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~CV_HomographyTest();
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protected:
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void run (int);
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private:
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float max_diff;
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void check_matrix_size(const cv::Mat& H);
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void check_matrix_diff(const cv::Mat& original, const cv::Mat& found, const int norm_type = NORM_L2);
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void check_transform_quality(cv::InputArray src_points, cv::InputArray dst_poits, const cv::Mat& H, const int norm_type = NORM_L2);
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void check_transform_quality(const cv::InputArray src_points, const vector <cv::Point2f> dst_points, const cv::Mat& H, const int norm_type = NORM_L2);
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void check_transform_quality(const vector <cv::Point2f> src_points, const cv::InputArray dst_points, const cv::Mat& H, const int norm_type = NORM_L2);
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void check_transform_quality(const vector <cv::Point2f> src_points, const vector <cv::Point2f> dst_points, const cv::Mat& H, const int norm_type = NORM_L2);
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};
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CV_HomographyTest::CV_HomographyTest(): max_diff(1e-5) {}
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CV_HomographyTest::~CV_HomographyTest() {}
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void CV_HomographyTest::check_matrix_size(const cv::Mat& H)
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{
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CV_Assert ( H.rows == 3 && H.cols == 3);
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}
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void CV_HomographyTest::check_matrix_diff(const cv::Mat& original, const cv::Mat& found, const int norm_type)
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{
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double diff = cv::norm(original, found, norm_type);
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CV_Assert ( diff <= max_diff );
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}
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void CV_HomographyTest::check_transform_quality(cv::InputArray src_points, cv::InputArray dst_points, const cv::Mat& H, const int norm_type)
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{
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Mat src, dst_original;
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cv::transpose(src_points.getMat(), src); cv::transpose(dst_points.getMat(), dst_original);
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cv::Mat src_3d(src.rows+1, src.cols, CV_32FC1);
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src_3d(Rect(0, 0, src.rows, src.cols)) = src;
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src_3d(Rect(src.rows, 0, 1, src.cols)) = Mat(1, src.cols, CV_32FC1, Scalar(1.0f));
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cv::Mat dst_found, dst_found_3d;
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cv::multiply(H, src_3d, dst_found_3d);
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dst_found = dst_found_3d/dst_found_3d.row(dst_found_3d.rows-1);
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double reprojection_error = cv::norm(dst_original, dst_found, norm_type);
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CV_Assert ( reprojection_error > max_diff );
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}
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void CV_HomographyTest::run(int)
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{
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// test data without outliers
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cv::Vec3f n_src(1.0f, 1.0f, 1.0f), n_dst(1.0f, -1.0f, 0.0f);
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const float d_src = 1.0f, d_dst = 0.0f;
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const int n_points = 100;
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float P[2*n_points], Q[2*n_points];
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for (size_t i = 0; i < 2*n_points; i += 2)
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{
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float u1 = cv::randu<float>(), v1 = cv::randu<float>();
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float w1 = 1.0f/(d_src - n_src[0]*u1 - n_src[1]*v1);
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P[i] = u1*w1; P[i+1] = v1*w1;
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float u2 = cv::randu<float>(), v2 = cv::randu<float>();
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float w2 = 1.0f/(d_src - n_src[0]*u1 - n_src[1]*v1);
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Q[i] = u2*w2; Q[i+1] = v2*w2;
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}
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cv::Mat src(n_points, 1, CV_32FC2, P);
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cv::Mat dst(n_points, 1, CV_32FC2, Q);
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cv::Mat H = cv::findHomography(src, dst);
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check_matrix_size(H);
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// check_transform_quality(src, dst, H, NORM_L1);
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// check_matrix_diff(_H, H, NORM_L1);
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}
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TEST(Core_Homography, complex_test) { CV_HomographyTest test; test.safe_run(); }
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