Open Source Computer Vision Library https://opencv.org/
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#include "test_precomp.hpp"
using namespace cv;
using namespace cv::gpu;
using namespace cvtest;
TEST(projectPoints, accuracy)
{
RNG& rng = TS::ptr()->get_rng();
Mat src = randomMat(rng, Size(1000, 1), CV_32FC3, 0, 10, false);
Mat rvec = randomMat(rng, Size(3, 1), CV_32F, 0, 1, false);
Mat tvec = randomMat(rng, Size(3, 1), CV_32F, 0, 1, false);
Mat camera_mat = randomMat(rng, Size(3, 3), CV_32F, 0, 1, false);
camera_mat.at<float>(0, 1) = 0.f;
camera_mat.at<float>(1, 0) = 0.f;
camera_mat.at<float>(2, 0) = 0.f;
camera_mat.at<float>(2, 1) = 0.f;
vector<Point2f> dst;
projectPoints(src, rvec, tvec, camera_mat, Mat(), dst);
GpuMat d_dst;
projectPoints(GpuMat(src), rvec, tvec, camera_mat, Mat(), d_dst);
ASSERT_EQ(dst.size(), (size_t)d_dst.cols);
ASSERT_EQ(1, d_dst.rows);
ASSERT_EQ(CV_32FC2, d_dst.type());
Mat h_dst(d_dst);
for (size_t i = 0; i < dst.size(); ++i)
{
Point2f res_gold = dst[i];
Point2f res_actual = h_dst.at<Point2f>(0, i);
Point2f err = res_actual - res_gold;
ASSERT_LT(err.dot(err) / res_gold.dot(res_gold), 1e-3f);
}
}
TEST(transformPoints, accuracy)
{
RNG& rng = TS::ptr()->get_rng();
Mat src = randomMat(rng, Size(1000, 1), CV_32FC3, 0, 10, false);
Mat rvec = randomMat(rng, Size(3, 1), CV_32F, 0, 1, false);
Mat tvec = randomMat(rng, Size(3, 1), CV_32F, 0, 1, false);
GpuMat d_dst;
transformPoints(GpuMat(src), rvec, tvec, d_dst);
ASSERT_TRUE(src.size() == d_dst.size());
ASSERT_EQ(src.type(), d_dst.type());
Mat h_dst(d_dst);
Mat rot;
Rodrigues(rvec, rot);
for (int i = 0; i < h_dst.cols; ++i)
{
Point3f p = src.at<Point3f>(0, i);
Point3f res_gold(
rot.at<float>(0, 0) * p.x + rot.at<float>(0, 1) * p.y + rot.at<float>(0, 2) * p.z + tvec.at<float>(0, 0),
rot.at<float>(1, 0) * p.x + rot.at<float>(1, 1) * p.y + rot.at<float>(1, 2) * p.z + tvec.at<float>(0, 1),
rot.at<float>(2, 0) * p.x + rot.at<float>(2, 1) * p.y + rot.at<float>(2, 2) * p.z + tvec.at<float>(0, 2));
Point3f res_actual = h_dst.at<Point3f>(0, i);
Point3f err = res_actual - res_gold;
ASSERT_LT(err.dot(err) / res_gold.dot(res_gold), 1e-3f);
}
}
TEST(solvePnPRansac, accuracy)
{
RNG& rng = TS::ptr()->get_rng();
const int num_points = 5000;
Mat object = randomMat(rng, Size(num_points, 1), CV_32FC3, 0, 100, false);
Mat camera_mat = randomMat(rng, Size(3, 3), CV_32F, 0.5, 1, false);
camera_mat.at<float>(0, 1) = 0.f;
camera_mat.at<float>(1, 0) = 0.f;
camera_mat.at<float>(2, 0) = 0.f;
camera_mat.at<float>(2, 1) = 0.f;
Mat rvec_gold = randomMat(rng, Size(3, 1), CV_32F, 0, 1, false);
Mat tvec_gold = randomMat(rng, Size(3, 1), CV_32F, 0, 1, false);
vector<Point2f> image_vec;
projectPoints(object, rvec_gold, tvec_gold, camera_mat, Mat(), image_vec);
Mat image(1, image_vec.size(), CV_32FC2, &image_vec[0]);
Mat rvec, tvec;
vector<int> inliers;
gpu::solvePnPRansac(object, image, camera_mat, Mat(), rvec, tvec, false, 200, 2.f, 100, &inliers);
ASSERT_LE(norm(rvec - rvec_gold), 1e-3f);
ASSERT_LE(norm(tvec - tvec_gold), 1e-3f);
}