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Commit 4cfc9dc6 authored by Alexander Reshetnikov's avatar Alexander Reshetnikov
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fixed bag in the checking size of matrix and vector for eigen test; all eigen… 

fixed bag in the checking size of matrix and vector for eigen test; all eigen test execution was checked: it works correctly; added first version of homography test for C++ interface
parent c29ea105
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Showing with 118 additions and 27 deletions
modules/calib3d/test/test_homography.cpp 0 → 100644
View file @ 4cfc9dc6
#include "test_precomp.hpp"
using namespace cv;
using namespace std;
class CV_HomographyTest: public cvtest::BaseTest
{
public:
CV_HomographyTest();
~CV_HomographyTest();
protected:
void run (int);
private:
float max_diff;
void check_matrix_size(const cv::Mat& H);
void check_matrix_diff(const cv::Mat& original, const cv::Mat& found, const int norm_type = NORM_L2);
void check_transform_quality(cv::InputArray src_points, cv::InputArray dst_poits, const cv::Mat& H, const int norm_type = NORM_L2);
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);
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);
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);
};
CV_HomographyTest::CV_HomographyTest(): max_diff(1e-5) {}
CV_HomographyTest::~CV_HomographyTest() {}
void CV_HomographyTest::check_matrix_size(const cv::Mat& H)
{
CV_Assert ( H.rows == 3 && H.cols == 3);
}
void CV_HomographyTest::check_matrix_diff(const cv::Mat& original, const cv::Mat& found, const int norm_type)
{
double diff = cv::norm(original, found, norm_type);
CV_Assert ( diff <= max_diff );
}
void CV_HomographyTest::check_transform_quality(cv::InputArray src_points, cv::InputArray dst_points, const cv::Mat& H, const int norm_type)
{
Mat src, dst_original;
cv::transpose(src_points.getMat(), src); cv::transpose(dst_points.getMat(), dst_original);
cv::Mat src_3d(src.rows+1, src.cols, CV_32FC1);
src_3d(Rect(0, 0, src.rows, src.cols)) = src;
src_3d(Rect(src.rows, 0, 1, src.cols)) = Mat(1, src.cols, CV_32FC1, Scalar(1.0f));
cv::Mat dst_found, dst_found_3d;
cv::multiply(H, src_3d, dst_found_3d);
dst_found = dst_found_3d/dst_found_3d.row(dst_found_3d.rows-1);
double reprojection_error = cv::norm(dst_original, dst_found, norm_type);
CV_Assert ( reprojection_error > max_diff );
}
void CV_HomographyTest::run(int)
{
// test data without outliers
cv::Vec3f n_src(1.0f, 1.0f, 1.0f), n_dst(1.0f, -1.0f, 0.0f);
const float d_src = 1.0f, d_dst = 0.0f;
const int n_points = 100;
float P[2*n_points], Q[2*n_points];
for (size_t i = 0; i < 2*n_points; i += 2)
{
float u1 = cv::randu<float>(), v1 = cv::randu<float>();
float w1 = 1.0f/(d_src - n_src[0]*u1 - n_src[1]*v1);
P[i] = u1*w1; P[i+1] = v1*w1;
float u2 = cv::randu<float>(), v2 = cv::randu<float>();
float w2 = 1.0f/(d_src - n_src[0]*u1 - n_src[1]*v1);
Q[i] = u2*w2; Q[i+1] = v2*w2;
}
cv::Mat src(n_points, 1, CV_32FC2, P);
cv::Mat dst(n_points, 1, CV_32FC2, Q);
cv::Mat H = cv::findHomography(src, dst);
check_matrix_size(H);
// check_transform_quality(src, dst, H, NORM_L1);
// check_matrix_diff(_H, H, NORM_L1);
}
TEST(Core_Homography, complex_test) { CV_HomographyTest test; test.safe_run(); }
\ No newline at end of file
modules/core/test/test_eigen.cpp
View file @ 4cfc9dc6
......@@ -3,7 +3,7 @@
using namespace cv;
using namespace std;
#define sign(a) a > 0 ? 1 : a < 0 ? 0 : -1
#define sign(a) a > 0 ? 1 : a == 0 ? 0 : -1
class Core_EigenTest: public cvtest::BaseTest
{
......@@ -25,23 +25,23 @@ class Core_EigenTest: public cvtest::BaseTest
const bool compute_eigen_vectors, const int values_type, const int norm_type);
};
Core_EigenTest::Core_EigenTest() : eps_val_32(1e-6), eps_vec_32(1e-5), eps_val_64(1e-12), eps_vec_64(1e-11) {}
Core_EigenTest::Core_EigenTest() : eps_val_32(1e-3), eps_vec_32(1e-2), eps_val_64(1e-5), eps_vec_64(1e-4) {}
Core_EigenTest::~Core_EigenTest() {}
void Core_EigenTest::check_pair_count(const cv::Mat& src, const cv::Mat& evalues, int low_index, int high_index)
{
int n = src.rows, s = sign(high_index);
CV_Assert(evalues.rows == n - (low_index+1) - ((int)((n/2.0)*(s*s-s)) + (1+s-s*s)*(n - (high_index+1))) && evalues.cols == 1);
CV_Assert ( evalues.rows == n - max<int>(0, low_index) - ((int)((n/2.0)*(s*s-s)) + (1+s-s*s)*(n - (high_index+1))) && evalues.cols == 1);
}
void Core_EigenTest::check_pair_count(const cv::Mat& src, const cv::Mat& evalues, const cv::Mat& evectors, int low_index, int high_index)
{
int n = src.rows, s = sign(high_index);
int right_eigen_pair_count = n - (low_index+1) - ((int)((n/2.0)*(s*s-s)) + (1+s-s*s)*(n - (high_index+1)));
CV_Assert( evectors.rows == right_eigen_pair_count &&
evectors.cols == right_eigen_pair_count &&
evalues.rows == right_eigen_pair_count &&
evalues.cols == 1);
int right_eigen_pair_count = n - max<int>(0, low_index) - ((int)((n/2.0)*(s*s-s)) + (1+s-s*s)*(n - (high_index+1)));
CV_Assert ( evectors.rows == right_eigen_pair_count &&
evectors.cols == right_eigen_pair_count &&
evalues.rows == right_eigen_pair_count &&
evalues.cols == 1 );
}
bool Core_EigenTest::check_diff(const cv::Mat& original_values, const cv::Mat& original_vectors,
......@@ -85,23 +85,23 @@ void Core_EigenTest::run(int)
// tests data
float sym_matrix[DIM][DIM] = { { 0.0f, 1.0f, 0.0f },
{ 1.0f, 0.0f, 1.0f },
{ 0.0f, 1.0f, 0.0f } }; // source symmerical matrix
float sym_matrix[DIM*DIM] = { 0.0f, 1.0f, 0.0f,
1.0f, 0.0f, 1.0f,
0.0f, 1.0f, 0.0f }; // source symmerical matrix
float _eval[DIM] = { sqrt(2.0f), 0.0f, -sqrt(2.0f) }; // eigen values of 3*3 matrix
float _eval[DIM] = { sqrt(2.0f), 0.0f, -sqrt(2.0f) }; // eigen values of 3*3 matrix
float _evec[DIM][DIM] = { { 1.0f, sqrt(2.0f), 1.0f },
{ -1.0f, 0.0f, 1.0f },
{ 1.0f, -sqrt(2.0f), 1.0f } }; // eigen vectors of source matrix
float _evec[DIM*DIM] = { 0.5f, 0.5f*sqrt(2.0f), 0.5f,
-0.5f*sqrt(2.0f), 0.0f, 0.5f*sqrt(2.0f),
0.5f, -0.5f*sqrt(2.0f), 0.5f }; // eigen vectors of source matrix
// initializing Mat-objects
cv::Mat eigen_values, eigen_vectors;
cv::Mat src_32(DIM, DIM, CV_32FC1, (void*)&sym_matrix[0]);
cv::Mat eval_32(DIM, 1, CV_32FC1, (void*)&_eval);
cv::Mat evec_32(DIM, DIM, CV_32FC1, (void*)&_evec[0]);
cv::Mat src_32(DIM, DIM, CV_32FC1, sym_matrix);
cv::Mat eval_32(DIM, 1, CV_32FC1, _eval);
cv::Mat evec_32(DIM, DIM, CV_32FC1, _evec);
cv::eigen(src_32, true, eigen_values, eigen_vectors);
......@@ -134,13 +134,15 @@ void Core_EigenTest::run(int)
if (!check_diff(eval_32, evec_32, eigen_values, eigen_vectors, false, CV_32FC1, NORM_L1)) return;
if (!check_diff(eval_32, evec_32, eigen_values, eigen_vectors, false, CV_32FC1, NORM_L2)) return;
if (!check_diff(eval_32, evec_32, eigen_values, eigen_vectors, false, CV_32FC1, NORM_INF)) return;
cv::Mat src_64(DIM, DIM, CV_64FC1, (void*)&sym_matrix[0]);
cv::Mat eval_64(DIM, 1, CV_64FC1, (void*)&_eval);
cv::Mat evec_64(DIM, DIM, CV_64FC1, (void*)&_evec[0]);
cv::Mat src_64(DIM, DIM, CV_64FC1, sym_matrix);
cv::Mat eval_64(DIM, 1, CV_64FC1, _eval);
cv::Mat evec_64(DIM, DIM, CV_64FC1, _evec);
cv::eigen(src_64, true, eigen_values, eigen_vectors);
check_pair_count(src_64, eigen_values, eigen_vectors);
if (!check_diff(eval_64, evec_64, eigen_values, eigen_vectors, true, CV_64FC1, NORM_L1)) return;
if (!check_diff(eval_64, evec_64, eigen_values, eigen_vectors, true, CV_64FC1, NORM_L2)) return;
if (!check_diff(eval_64, evec_64, eigen_values, eigen_vectors, true, CV_64FC1, NORM_INF)) return;
......@@ -169,12 +171,12 @@ void Core_EigenTest::run(int)
if (!check_diff(eval_64, evec_64, eigen_values, eigen_vectors, false, CV_64FC1, NORM_L2)) return;
if (!check_diff(eval_64, evec_64, eigen_values, eigen_vectors, false, CV_64FC1, NORM_INF)) return;
const int low_index = 2, high_index = 3;
const int low_index = 1, high_index = 2;
cv::Mat submat_val_32(eval_32.rowRange(low_index, high_index));
cv::Mat submat_vec_32(evec_32.rowRange(low_index, high_index));
cv::eigen(src_32, eigen_values, low_index, high_index);
cv::eigen(src_32, eigen_values, low_index, high_index);
check_pair_count(src_32, eigen_values, eigen_vectors, low_index, high_index);
if (!check_diff(submat_val_32, submat_vec_32, eigen_values, eigen_vectors, false, CV_32FC1, NORM_L1)) return;
......@@ -188,7 +190,7 @@ void Core_EigenTest::run(int)
if (!check_diff(submat_val_32, submat_vec_32, eigen_values, eigen_vectors, true, CV_32FC1, NORM_L1)) return;
if (!check_diff(submat_val_32, submat_vec_32, eigen_values, eigen_vectors, true, CV_32FC1, NORM_L2)) return;
if (!check_diff(submat_val_32, submat_vec_32, eigen_values, eigen_vectors, true, CV_32FC1, NORM_INF)) return;
cv::Mat submat_val_64(eval_64.rowRange(low_index, high_index));
cv::Mat submat_vec_64(evec_64.rowRange(low_index, high_index));
......@@ -209,5 +211,5 @@ void Core_EigenTest::run(int)
if (!check_diff(submat_val_64, submat_vec_64, eigen_values, eigen_vectors, true, CV_64FC1, NORM_INF)) return;
}
TEST(Core_Eigen, quality) { Core_EigenTest test; test.safe_run(); }
TEST(Core_Eigen, accuracy) { Core_EigenTest test; test.safe_run(); }
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