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Visual Studio 2015 warning and test fixes

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This commit is contained in:
Maksim Shabunin
2015-10-16 17:10:00 +03:00
parent 1648e9292c
commit 6e9d0d9a0c
54 changed files with 242 additions and 229 deletions
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106
modules/calib3d/test/test_fisheye.cpp
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@@ -101,15 +101,15 @@ TEST_F(fisheyeTest, projectPoints)
TEST_F(fisheyeTest, DISABLED_undistortImage)
{
cv::Matx33d K = this->K;
cv::Mat D = cv::Mat(this->D);
cv::Matx33d theK = this->K;
cv::Mat theD = cv::Mat(this->D);
std::string file = combine(datasets_repository_path, "/calib-3_stereo_from_JY/left/stereo_pair_014.jpg");
cv::Matx33d newK = K;
cv::Matx33d newK = theK;
cv::Mat distorted = cv::imread(file), undistorted;
{
newK(0, 0) = 100;
newK(1, 1) = 100;
cv::fisheye::undistortImage(distorted, undistorted, K, D, newK);
cv::fisheye::undistortImage(distorted, undistorted, theK, theD, newK);
cv::Mat correct = cv::imread(combine(datasets_repository_path, "new_f_100.png"));
if (correct.empty())
CV_Assert(cv::imwrite(combine(datasets_repository_path, "new_f_100.png"), undistorted));
@@ -118,8 +118,8 @@ TEST_F(fisheyeTest, DISABLED_undistortImage)
}
{
double balance = 1.0;
cv::fisheye::estimateNewCameraMatrixForUndistortRectify(K, D, distorted.size(), cv::noArray(), newK, balance);
cv::fisheye::undistortImage(distorted, undistorted, K, D, newK);
cv::fisheye::estimateNewCameraMatrixForUndistortRectify(theK, theD, distorted.size(), cv::noArray(), newK, balance);
cv::fisheye::undistortImage(distorted, undistorted, theK, theD, newK);
cv::Mat correct = cv::imread(combine(datasets_repository_path, "balance_1.0.png"));
if (correct.empty())
CV_Assert(cv::imwrite(combine(datasets_repository_path, "balance_1.0.png"), undistorted));
@@ -129,8 +129,8 @@ TEST_F(fisheyeTest, DISABLED_undistortImage)
{
double balance = 0.0;
cv::fisheye::estimateNewCameraMatrixForUndistortRectify(K, D, distorted.size(), cv::noArray(), newK, balance);
cv::fisheye::undistortImage(distorted, undistorted, K, D, newK);
cv::fisheye::estimateNewCameraMatrixForUndistortRectify(theK, theD, distorted.size(), cv::noArray(), newK, balance);
cv::fisheye::undistortImage(distorted, undistorted, theK, theD, newK);
cv::Mat correct = cv::imread(combine(datasets_repository_path, "balance_0.0.png"));
if (correct.empty())
CV_Assert(cv::imwrite(combine(datasets_repository_path, "balance_0.0.png"), undistorted));
@@ -143,7 +143,7 @@ TEST_F(fisheyeTest, jacobians)
{
int n = 10;
cv::Mat X(1, n, CV_64FC3);
cv::Mat om(3, 1, CV_64F), T(3, 1, CV_64F);
cv::Mat om(3, 1, CV_64F), theT(3, 1, CV_64F);
cv::Mat f(2, 1, CV_64F), c(2, 1, CV_64F);
cv::Mat k(4, 1, CV_64F);
double alpha;
@@ -156,8 +156,8 @@ TEST_F(fisheyeTest, jacobians)
r.fill(om, cv::RNG::NORMAL, 0, 1);
om = cv::abs(om);
r.fill(T, cv::RNG::NORMAL, 0, 1);
T = cv::abs(T); T.at<double>(2) = 4; T *= 10;
r.fill(theT, cv::RNG::NORMAL, 0, 1);
theT = cv::abs(theT); theT.at<double>(2) = 4; theT *= 10;
r.fill(f, cv::RNG::NORMAL, 0, 1);
f = cv::abs(f) * 1000;
@@ -171,19 +171,19 @@ TEST_F(fisheyeTest, jacobians)
alpha = 0.01*r.gaussian(1);
cv::Mat x1, x2, xpred;
cv::Matx33d K(f.at<double>(0), alpha * f.at<double>(0), c.at<double>(0),
cv::Matx33d theK(f.at<double>(0), alpha * f.at<double>(0), c.at<double>(0),
0, f.at<double>(1), c.at<double>(1),
0, 0, 1);
cv::Mat jacobians;
cv::fisheye::projectPoints(X, x1, om, T, K, k, alpha, jacobians);
cv::fisheye::projectPoints(X, x1, om, theT, theK, k, alpha, jacobians);
//test on T:
cv::Mat dT(3, 1, CV_64FC1);
r.fill(dT, cv::RNG::NORMAL, 0, 1);
dT *= 1e-9*cv::norm(T);
cv::Mat T2 = T + dT;
cv::fisheye::projectPoints(X, x2, om, T2, K, k, alpha, cv::noArray());
dT *= 1e-9*cv::norm(theT);
cv::Mat T2 = theT + dT;
cv::fisheye::projectPoints(X, x2, om, T2, theK, k, alpha, cv::noArray());
xpred = x1 + cv::Mat(jacobians.colRange(11,14) * dT).reshape(2, 1);
CV_Assert (cv::norm(x2 - xpred) < 1e-10);
@@ -192,7 +192,7 @@ TEST_F(fisheyeTest, jacobians)
r.fill(dom, cv::RNG::NORMAL, 0, 1);
dom *= 1e-9*cv::norm(om);
cv::Mat om2 = om + dom;
cv::fisheye::projectPoints(X, x2, om2, T, K, k, alpha, cv::noArray());
cv::fisheye::projectPoints(X, x2, om2, theT, theK, k, alpha, cv::noArray());
xpred = x1 + cv::Mat(jacobians.colRange(8,11) * dom).reshape(2, 1);
CV_Assert (cv::norm(x2 - xpred) < 1e-10);
@@ -200,8 +200,8 @@ TEST_F(fisheyeTest, jacobians)
cv::Mat df(2, 1, CV_64FC1);
r.fill(df, cv::RNG::NORMAL, 0, 1);
df *= 1e-9*cv::norm(f);
cv::Matx33d K2 = K + cv::Matx33d(df.at<double>(0), df.at<double>(0) * alpha, 0, 0, df.at<double>(1), 0, 0, 0, 0);
cv::fisheye::projectPoints(X, x2, om, T, K2, k, alpha, cv::noArray());
cv::Matx33d K2 = theK + cv::Matx33d(df.at<double>(0), df.at<double>(0) * alpha, 0, 0, df.at<double>(1), 0, 0, 0, 0);
cv::fisheye::projectPoints(X, x2, om, theT, K2, k, alpha, cv::noArray());
xpred = x1 + cv::Mat(jacobians.colRange(0,2) * df).reshape(2, 1);
CV_Assert (cv::norm(x2 - xpred) < 1e-10);
@@ -209,8 +209,8 @@ TEST_F(fisheyeTest, jacobians)
cv::Mat dc(2, 1, CV_64FC1);
r.fill(dc, cv::RNG::NORMAL, 0, 1);
dc *= 1e-9*cv::norm(c);
K2 = K + cv::Matx33d(0, 0, dc.at<double>(0), 0, 0, dc.at<double>(1), 0, 0, 0);
cv::fisheye::projectPoints(X, x2, om, T, K2, k, alpha, cv::noArray());
K2 = theK + cv::Matx33d(0, 0, dc.at<double>(0), 0, 0, dc.at<double>(1), 0, 0, 0);
cv::fisheye::projectPoints(X, x2, om, theT, K2, k, alpha, cv::noArray());
xpred = x1 + cv::Mat(jacobians.colRange(2,4) * dc).reshape(2, 1);
CV_Assert (cv::norm(x2 - xpred) < 1e-10);
@@ -219,7 +219,7 @@ TEST_F(fisheyeTest, jacobians)
r.fill(dk, cv::RNG::NORMAL, 0, 1);
dk *= 1e-9*cv::norm(k);
cv::Mat k2 = k + dk;
cv::fisheye::projectPoints(X, x2, om, T, K, k2, alpha, cv::noArray());
cv::fisheye::projectPoints(X, x2, om, theT, theK, k2, alpha, cv::noArray());
xpred = x1 + cv::Mat(jacobians.colRange(4,8) * dk).reshape(2, 1);
CV_Assert (cv::norm(x2 - xpred) < 1e-10);
@@ -228,8 +228,8 @@ TEST_F(fisheyeTest, jacobians)
r.fill(dalpha, cv::RNG::NORMAL, 0, 1);
dalpha *= 1e-9*cv::norm(f);
double alpha2 = alpha + dalpha.at<double>(0);
K2 = K + cv::Matx33d(0, f.at<double>(0) * dalpha.at<double>(0), 0, 0, 0, 0, 0, 0, 0);
cv::fisheye::projectPoints(X, x2, om, T, K, k, alpha2, cv::noArray());
K2 = theK + cv::Matx33d(0, f.at<double>(0) * dalpha.at<double>(0), 0, 0, 0, 0, 0, 0, 0);
cv::fisheye::projectPoints(X, x2, om, theT, theK, k, alpha2, cv::noArray());
xpred = x1 + cv::Mat(jacobians.col(14) * dalpha).reshape(2, 1);
CV_Assert (cv::norm(x2 - xpred) < 1e-10);
}
@@ -259,14 +259,14 @@ TEST_F(fisheyeTest, Calibration)
flag |= cv::fisheye::CALIB_CHECK_COND;
flag |= cv::fisheye::CALIB_FIX_SKEW;
cv::Matx33d K;
cv::Vec4d D;
cv::Matx33d theK;
cv::Vec4d theD;
cv::fisheye::calibrate(objectPoints, imagePoints, imageSize, K, D,
cv::fisheye::calibrate(objectPoints, imagePoints, imageSize, theK, theD,
cv::noArray(), cv::noArray(), flag, cv::TermCriteria(3, 20, 1e-6));
EXPECT_MAT_NEAR(K, this->K, 1e-10);
EXPECT_MAT_NEAR(D, this->D, 1e-10);
EXPECT_MAT_NEAR(theK, this->K, 1e-10);
EXPECT_MAT_NEAR(theD, this->D, 1e-10);
}
TEST_F(fisheyeTest, Homography)
@@ -303,15 +303,15 @@ TEST_F(fisheyeTest, Homography)
int Np = imagePointsNormalized.cols;
cv::calcCovarMatrix(_objectPoints, covObjectPoints, objectPointsMean, cv::COVAR_NORMAL | cv::COVAR_COLS);
cv::SVD svd(covObjectPoints);
cv::Mat R(svd.vt);
cv::Mat theR(svd.vt);
if (cv::norm(R(cv::Rect(2, 0, 1, 2))) < 1e-6)
R = cv::Mat::eye(3,3, CV_64FC1);
if (cv::determinant(R) < 0)
R = -R;
if (cv::norm(theR(cv::Rect(2, 0, 1, 2))) < 1e-6)
theR = cv::Mat::eye(3,3, CV_64FC1);
if (cv::determinant(theR) < 0)
theR = -theR;
cv::Mat T = -R * objectPointsMean;
cv::Mat X_new = R * _objectPoints + T * cv::Mat::ones(1, Np, CV_64FC1);
cv::Mat theT = -theR * objectPointsMean;
cv::Mat X_new = theR * _objectPoints + theT * cv::Mat::ones(1, Np, CV_64FC1);
cv::Mat H = cv::internal::ComputeHomography(imagePointsNormalized, X_new.rowRange(0, 2));
cv::Mat M = cv::Mat::ones(3, X_new.cols, CV_64FC1);
@@ -355,19 +355,19 @@ TEST_F(fisheyeTest, EtimateUncertainties)
flag |= cv::fisheye::CALIB_CHECK_COND;
flag |= cv::fisheye::CALIB_FIX_SKEW;
cv::Matx33d K;
cv::Vec4d D;
cv::Matx33d theK;
cv::Vec4d theD;
std::vector<cv::Vec3d> rvec;
std::vector<cv::Vec3d> tvec;
cv::fisheye::calibrate(objectPoints, imagePoints, imageSize, K, D,
cv::fisheye::calibrate(objectPoints, imagePoints, imageSize, theK, theD,
rvec, tvec, flag, cv::TermCriteria(3, 20, 1e-6));
cv::internal::IntrinsicParams param, errors;
cv::Vec2d err_std;
double thresh_cond = 1e6;
int check_cond = 1;
param.Init(cv::Vec2d(K(0,0), K(1,1)), cv::Vec2d(K(0,2), K(1, 2)), D);
param.Init(cv::Vec2d(theK(0,0), theK(1,1)), cv::Vec2d(theK(0,2), theK(1, 2)), theD);
param.isEstimate = std::vector<int>(9, 1);
param.isEstimate[4] = 0;
@@ -399,12 +399,12 @@ TEST_F(fisheyeTest, rectify)
cv::Matx33d K1 = this->K, K2 = K1;
cv::Mat D1 = cv::Mat(this->D), D2 = D1;
cv::Vec3d T = this->T;
cv::Matx33d R = this->R;
cv::Vec3d theT = this->T;
cv::Matx33d theR = this->R;
double balance = 0.0, fov_scale = 1.1;
cv::Mat R1, R2, P1, P2, Q;
cv::fisheye::stereoRectify(K1, D1, K2, D2, calibration_size, R, T, R1, R2, P1, P2, Q,
cv::fisheye::stereoRectify(K1, D1, K2, D2, calibration_size, theR, theT, R1, R2, P1, P2, Q,
cv::CALIB_ZERO_DISPARITY, requested_size, balance, fov_scale);
cv::Mat lmapx, lmapy, rmapx, rmapy;
@@ -468,8 +468,8 @@ TEST_F(fisheyeTest, stereoCalibrate)
fs_object[cv::format("image_%d", i )] >> objectPoints[i];
fs_object.release();
cv::Matx33d K1, K2, R;
cv::Vec3d T;
cv::Matx33d K1, K2, theR;
cv::Vec3d theT;
cv::Vec4d D1, D2;
int flag = 0;
@@ -479,7 +479,7 @@ TEST_F(fisheyeTest, stereoCalibrate)
// flag |= cv::fisheye::CALIB_FIX_INTRINSIC;
cv::fisheye::stereoCalibrate(objectPoints, leftPoints, rightPoints,
K1, D1, K2, D2, imageSize, R, T, flag,
K1, D1, K2, D2, imageSize, theR, theT, flag,
cv::TermCriteria(3, 12, 0));
cv::Matx33d R_correct( 0.9975587205950972, 0.06953016383322372, 0.006492709911733523,
@@ -497,8 +497,8 @@ TEST_F(fisheyeTest, stereoCalibrate)
cv::Vec4d D1_correct (-7.44253716539556e-05, -0.00702662033932424, 0.00737569823650885, -0.00342230256441771);
cv::Vec4d D2_correct (-0.0130785435677431, 0.0284434505383497, -0.0360333869900506, 0.0144724062347222);
EXPECT_MAT_NEAR(R, R_correct, 1e-10);
EXPECT_MAT_NEAR(T, T_correct, 1e-10);
EXPECT_MAT_NEAR(theR, R_correct, 1e-10);
EXPECT_MAT_NEAR(theT, T_correct, 1e-10);
EXPECT_MAT_NEAR(K1, K1_correct, 1e-10);
EXPECT_MAT_NEAR(K2, K2_correct, 1e-10);
@@ -536,8 +536,8 @@ TEST_F(fisheyeTest, stereoCalibrateFixIntrinsic)
fs_object[cv::format("image_%d", i )] >> objectPoints[i];
fs_object.release();
cv::Matx33d R;
cv::Vec3d T;
cv::Matx33d theR;
cv::Vec3d theT;
int flag = 0;
flag |= cv::fisheye::CALIB_RECOMPUTE_EXTRINSIC;
@@ -557,7 +557,7 @@ TEST_F(fisheyeTest, stereoCalibrateFixIntrinsic)
cv::Vec4d D2 (-0.0130785435677431, 0.0284434505383497, -0.0360333869900506, 0.0144724062347222);
cv::fisheye::stereoCalibrate(objectPoints, leftPoints, rightPoints,
K1, D1, K2, D2, imageSize, R, T, flag,
K1, D1, K2, D2, imageSize, theR, theT, flag,
cv::TermCriteria(3, 12, 0));
cv::Matx33d R_correct( 0.9975587205950972, 0.06953016383322372, 0.006492709911733523,
@@ -566,8 +566,8 @@ TEST_F(fisheyeTest, stereoCalibrateFixIntrinsic)
cv::Vec3d T_correct(-0.099402724724121, 0.00270812139265413, 0.00129330292472699);
EXPECT_MAT_NEAR(R, R_correct, 1e-10);
EXPECT_MAT_NEAR(T, T_correct, 1e-10);
EXPECT_MAT_NEAR(theR, R_correct, 1e-10);
EXPECT_MAT_NEAR(theT, T_correct, 1e-10);
}
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////