mirror of
https://github.com/opencv/opencv.git
synced 2024-12-24 00:17:59 +08:00
97 lines
3.1 KiB
C++
97 lines
3.1 KiB
C++
|
#include "test_precomp.hpp"
|
||
|
#include <string>
|
||
|
|
||
|
using namespace cv;
|
||
|
using namespace std;
|
||
|
|
||
|
class CV_UndistortTest : public cvtest::BaseTest
|
||
|
{
|
||
|
public:
|
||
|
CV_UndistortTest();
|
||
|
~CV_UndistortTest();
|
||
|
protected:
|
||
|
void run(int);
|
||
|
private:
|
||
|
void generate3DPointCloud(vector<Point3f>& points, Point3f pmin = Point3f(-1,
|
||
|
-1, 5), Point3f pmax = Point3f(1, 1, 10));
|
||
|
void generateCameraMatrix(Mat& cameraMatrix);
|
||
|
void generateDistCoeffs(Mat& distCoeffs, int count);
|
||
|
|
||
|
double thresh;
|
||
|
RNG rng;
|
||
|
};
|
||
|
|
||
|
CV_UndistortTest::CV_UndistortTest()
|
||
|
{
|
||
|
thresh = 1.0e-2;
|
||
|
}
|
||
|
CV_UndistortTest::~CV_UndistortTest() {}
|
||
|
|
||
|
void CV_UndistortTest::generate3DPointCloud(vector<Point3f>& points, Point3f pmin, Point3f pmax)
|
||
|
{
|
||
|
const Point3f delta = pmax - pmin;
|
||
|
for (size_t i = 0; i < points.size(); i++)
|
||
|
{
|
||
|
Point3f p(float(rand()) / RAND_MAX, float(rand()) / RAND_MAX,
|
||
|
float(rand()) / RAND_MAX);
|
||
|
p.x *= delta.x;
|
||
|
p.y *= delta.y;
|
||
|
p.z *= delta.z;
|
||
|
p = p + pmin;
|
||
|
points[i] = p;
|
||
|
}
|
||
|
}
|
||
|
void CV_UndistortTest::generateCameraMatrix(Mat& cameraMatrix)
|
||
|
{
|
||
|
const double fcMinVal = 1e-3;
|
||
|
const double fcMaxVal = 100;
|
||
|
cameraMatrix.create(3, 3, CV_64FC1);
|
||
|
cameraMatrix.setTo(Scalar(0));
|
||
|
cameraMatrix.at<double>(0,0) = rng.uniform(fcMinVal, fcMaxVal);
|
||
|
cameraMatrix.at<double>(1,1) = rng.uniform(fcMinVal, fcMaxVal);
|
||
|
cameraMatrix.at<double>(0,2) = rng.uniform(fcMinVal, fcMaxVal);
|
||
|
cameraMatrix.at<double>(1,2) = rng.uniform(fcMinVal, fcMaxVal);
|
||
|
cameraMatrix.at<double>(2,2) = 1;
|
||
|
}
|
||
|
void CV_UndistortTest::generateDistCoeffs(Mat& distCoeffs, int count)
|
||
|
{
|
||
|
distCoeffs = Mat::zeros(count, 1, CV_64FC1);
|
||
|
for (int i = 0; i < count; i++)
|
||
|
distCoeffs.at<double>(i,0) = rng.uniform(0.0, 1.0e-3);
|
||
|
}
|
||
|
|
||
|
void CV_UndistortTest::run(int /* start_from */)
|
||
|
{
|
||
|
Mat intrinsics, distCoeffs;
|
||
|
generateCameraMatrix(intrinsics);
|
||
|
vector<Point3f> points(500);
|
||
|
generate3DPointCloud(points);
|
||
|
vector<Point2f> projectedPoints;
|
||
|
projectedPoints.resize(points.size());
|
||
|
|
||
|
int modelMembersCount[] = {4,5,8};
|
||
|
for (int idx = 0; idx < 3; idx++)
|
||
|
{
|
||
|
generateDistCoeffs(distCoeffs, modelMembersCount[idx]);
|
||
|
projectPoints(Mat(points), Mat::zeros(3,1,CV_64FC1), Mat::zeros(3,1,CV_64FC1), intrinsics, distCoeffs, projectedPoints);
|
||
|
|
||
|
vector<Point2f> realUndistortedPoints;
|
||
|
projectPoints(Mat(points), Mat::zeros(3,1,CV_64FC1), Mat::zeros(3,1,CV_64FC1), intrinsics, Mat::zeros(4,1,CV_64FC1), realUndistortedPoints);
|
||
|
|
||
|
Mat undistortedPoints;
|
||
|
undistortPoints(Mat(projectedPoints), undistortedPoints, intrinsics, distCoeffs);
|
||
|
|
||
|
Mat p;
|
||
|
perspectiveTransform(undistortedPoints, p, intrinsics);
|
||
|
undistortedPoints = p;
|
||
|
double diff = norm(Mat(realUndistortedPoints), undistortedPoints);
|
||
|
if (diff > thresh)
|
||
|
{
|
||
|
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
|
||
|
return;
|
||
|
}
|
||
|
ts->set_failed_test_info(cvtest::TS::OK);
|
||
|
}
|
||
|
}
|
||
|
|
||
|
TEST(Calib3d_Undistort, accuracy) { CV_UndistortTest test; test.safe_run(); }
|