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use static assertation where suitable
This commit is contained in:
marina.kolpakova
parent
5c1c13e745
commit
4096b54560
@ -1079,7 +1079,7 @@ protected:
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void run_func();
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void prepare_to_validation( int );
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double sampson_error(const double* f, double x1, double y1, double x2, double y2);
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double sampson_error(const double* f, double x1, double y1, double x2, double y2);
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int method;
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int img_size;
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@ -1145,9 +1145,8 @@ void CV_EssentialMatTest::get_test_array_types_and_sizes( int /*test_case_idx*/,
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int pt_count = MAX(5, cvRound(exp(pt_count_exp)));
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dims = cvtest::randInt(rng) % 2 + 2;
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dims = 2;
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dims = 2;
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method = CV_LMEDS << (cvtest::randInt(rng) % 2);
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types[INPUT][0] = CV_MAKETYPE(pt_depth, 1);
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@ -1192,11 +1191,11 @@ void CV_EssentialMatTest::get_test_array_types_and_sizes( int /*test_case_idx*/,
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sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize(3,1);
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types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_64FC1;
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sizes[OUTPUT][1] = sizes[REF_OUTPUT][1] = cvSize(pt_count,1);
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types[OUTPUT][1] = types[REF_OUTPUT][1] = CV_8UC1;
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types[OUTPUT][1] = types[REF_OUTPUT][1] = CV_8UC1;
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sizes[OUTPUT][2] = sizes[REF_OUTPUT][2] = cvSize(1,1);
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types[OUTPUT][2] = types[REF_OUTPUT][2] = CV_64FC1;
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sizes[OUTPUT][3] = sizes[REF_OUTPUT][3] = cvSize(1,1);
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types[OUTPUT][3] = types[REF_OUTPUT][3] = CV_8UC1;
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types[OUTPUT][3] = types[REF_OUTPUT][3] = CV_8UC1;
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}
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@ -1289,46 +1288,46 @@ int CV_EssentialMatTest::prepare_test_case( int test_case_idx )
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void CV_EssentialMatTest::run_func()
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{
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Mat _input0(test_mat[INPUT][0]), _input1(test_mat[INPUT][1]);
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Mat K(test_mat[INPUT][4]);
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double focal(K.at<double>(0, 0));
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cv::Point2d pp(K.at<double>(0, 2), K.at<double>(1, 2));
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Mat K(test_mat[INPUT][4]);
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double focal(K.at<double>(0, 0));
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cv::Point2d pp(K.at<double>(0, 2), K.at<double>(1, 2));
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RNG& rng = ts->get_rng();
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Mat E, mask1(test_mat[TEMP][1]);
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E = cv::findEssentialMat( _input0, _input1, focal, pp, method, 0.99, MAX(sigma*3, 0.0001), mask1 );
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if (E.rows > 3)
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E = cv::findEssentialMat( _input0, _input1, focal, pp, method, 0.99, MAX(sigma*3, 0.0001), mask1 );
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if (E.rows > 3)
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{
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int count = E.rows / 3;
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int row = (cvtest::randInt(rng) % count) * 3;
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E = E.rowRange(row, row + 3) * 1.0;
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int count = E.rows / 3;
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int row = (cvtest::randInt(rng) % count) * 3;
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E = E.rowRange(row, row + 3) * 1.0;
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}
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E.copyTo(test_mat[TEMP][0]);
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E.copyTo(test_mat[TEMP][0]);
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Mat R, t, mask2;
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recoverPose( E, _input0, _input1, R, t, focal, pp, mask2 );
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R.copyTo(test_mat[TEMP][2]);
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t.copyTo(test_mat[TEMP][3]);
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mask2.copyTo(test_mat[TEMP][4]);
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Mat R, t, mask2;
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recoverPose( E, _input0, _input1, R, t, focal, pp, mask2 );
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R.copyTo(test_mat[TEMP][2]);
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t.copyTo(test_mat[TEMP][3]);
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mask2.copyTo(test_mat[TEMP][4]);
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}
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double CV_EssentialMatTest::sampson_error(const double * f, double x1, double y1, double x2, double y2)
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{
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double Fx1[3] = {
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f[0] * x1 + f[1] * y1 + f[2],
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f[3] * x1 + f[4] * y1 + f[5],
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f[0] * x1 + f[1] * y1 + f[2],
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f[3] * x1 + f[4] * y1 + f[5],
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f[6] * x1 + f[7] * y1 + f[8]
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};
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};
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double Ftx2[3] = {
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f[0] * x2 + f[3] * y2 + f[6],
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f[1] * x2 + f[4] * y2 + f[7],
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f[0] * x2 + f[3] * y2 + f[6],
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f[1] * x2 + f[4] * y2 + f[7],
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f[2] * x2 + f[5] * y2 + f[8]
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};
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double x2tFx1 = Fx1[0] * x2 + Fx1[1] * y2 + Fx1[2];
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};
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double x2tFx1 = Fx1[0] * x2 + Fx1[1] * y2 + Fx1[2];
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double error = x2tFx1 * x2tFx1 / (Fx1[0] * Fx1[0] + Fx1[1] * Fx1[1] + Ftx2[0] * Ftx2[0] + Ftx2[1] * Ftx2[1]);
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error = sqrt(error);
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return error;
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double error = x2tFx1 * x2tFx1 / (Fx1[0] * Fx1[0] + Fx1[1] * Fx1[1] + Ftx2[0] * Ftx2[0] + Ftx2[1] * Ftx2[1]);
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error = sqrt(error);
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return error;
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}
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@ -1338,7 +1337,7 @@ void CV_EssentialMatTest::prepare_to_validation( int test_case_idx )
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const Mat& A = test_mat[INPUT][4];
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double f0[9], f[9], e[9];
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Mat F0(3, 3, CV_64FC1, f0), F(3, 3, CV_64F, f);
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Mat E(3, 3, CV_64F, e);
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Mat E(3, 3, CV_64F, e);
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Mat invA, R=Rt0.colRange(0, 3), T1, T2;
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@ -1362,7 +1361,7 @@ void CV_EssentialMatTest::prepare_to_validation( int test_case_idx )
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uchar* mtfm2 = test_mat[OUTPUT][1].data;
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double* e_prop1 = (double*)test_mat[REF_OUTPUT][0].data;
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double* e_prop2 = (double*)test_mat[OUTPUT][0].data;
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Mat E_prop2 = Mat(3, 1, CV_64F, e_prop2);
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Mat E_prop2 = Mat(3, 1, CV_64F, e_prop2);
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int i, pt_count = test_mat[INPUT][2].cols;
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Mat p1( 1, pt_count, CV_64FC2 );
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@ -1381,8 +1380,8 @@ void CV_EssentialMatTest::prepare_to_validation( int test_case_idx )
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double y1 = p1.at<Point2d>(i).y;
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double x2 = p2.at<Point2d>(i).x;
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double y2 = p2.at<Point2d>(i).y;
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// double t0 = sampson_error(f0, x1, y1, x2, y2);
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// double t = sampson_error(f, x1, y1, x2, y2);
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// double t0 = sampson_error(f0, x1, y1, x2, y2);
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// double t = sampson_error(f, x1, y1, x2, y2);
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double n1 = 1./sqrt(x1*x1 + y1*y1 + 1);
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double n2 = 1./sqrt(x2*x2 + y2*y2 + 1);
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double t0 = fabs(f0[0]*x2*x1 + f0[1]*x2*y1 + f0[2]*x2 +
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@ -1394,7 +1393,7 @@ void CV_EssentialMatTest::prepare_to_validation( int test_case_idx )
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mtfm1[i] = 1;
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mtfm2[i] = !status[i] || t0 > err_level || t < err_level;
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}
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e_prop1[0] = sqrt(0.5);
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e_prop1[1] = sqrt(0.5);
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e_prop1[2] = 0;
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@ -1402,26 +1401,26 @@ void CV_EssentialMatTest::prepare_to_validation( int test_case_idx )
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e_prop2[0] = 0;
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e_prop2[1] = 0;
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e_prop2[2] = 0;
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SVD::compute(E, E_prop2);
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SVD::compute(E, E_prop2);
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double* pose_prop1 = (double*)test_mat[REF_OUTPUT][2].data;
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double* pose_prop2 = (double*)test_mat[OUTPUT][2].data;
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double terr1 = norm(Rt0.col(3) / norm(Rt0.col(3)) + test_mat[TEMP][3]);
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double terr2 = norm(Rt0.col(3) / norm(Rt0.col(3)) - test_mat[TEMP][3]);
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Mat rvec;
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Rodrigues(Rt0.colRange(0, 3), rvec);
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pose_prop1[0] = 0;
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// No check for CV_LMeDS on translation. Since it
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// involves with some degraded problem, when data is exact inliers.
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pose_prop2[0] = method == CV_LMEDS || pt_count == 5 ? 0 : MIN(terr1, terr2);
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double* pose_prop1 = (double*)test_mat[REF_OUTPUT][2].data;
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double* pose_prop2 = (double*)test_mat[OUTPUT][2].data;
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double terr1 = norm(Rt0.col(3) / norm(Rt0.col(3)) + test_mat[TEMP][3]);
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double terr2 = norm(Rt0.col(3) / norm(Rt0.col(3)) - test_mat[TEMP][3]);
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Mat rvec;
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Rodrigues(Rt0.colRange(0, 3), rvec);
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pose_prop1[0] = 0;
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// No check for CV_LMeDS on translation. Since it
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// involves with some degraded problem, when data is exact inliers.
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pose_prop2[0] = method == CV_LMEDS || pt_count == 5 ? 0 : MIN(terr1, terr2);
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// int inliers_count = countNonZero(test_mat[TEMP][1]);
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// int good_count = countNonZero(test_mat[TEMP][4]);
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test_mat[OUTPUT][3] = true; //good_count >= inliers_count / 2;
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test_mat[REF_OUTPUT][3] = true;
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// int inliers_count = countNonZero(test_mat[TEMP][1]);
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// int good_count = countNonZero(test_mat[TEMP][4]);
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test_mat[OUTPUT][3] = true; //good_count >= inliers_count / 2;
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test_mat[REF_OUTPUT][3] = true;
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}
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@ -68,7 +68,7 @@ namespace cv
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//Rodrigues vector
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Affine3(const Vec3& rvec, const Vec3& t = Vec3::all(0));
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//Combines all contructors above. Supports 4x4, 3x3, 1x3, 3x1 sizes of data matrix
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explicit Affine3(const cv::Mat& data, const Vec3& t = Vec3::all(0));
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@ -79,13 +79,13 @@ namespace cv
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//Rotation matrix
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void rotation(const Mat3& R);
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//Rodrigues vector
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void rotation(const Vec3& rvec);
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//Combines rotation methods above. Suports 3x3, 1x3, 3x1 sizes of data matrix;
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void rotation(const Mat& data);
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//Euler angles
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void rotation(float_type alpha, float_type beta, float_type gamma);
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@ -218,7 +218,7 @@ template<typename T> inline void cv::Affine3<T>::rotation(const Vec3& rvec)
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template<typename T> inline void cv::Affine3<T>::rotation(const cv::Mat& data)
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{
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CV_Assert(data.type() == cv::DataType<T>::type);
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if (data.cols == 3 && data.rows == 3)
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{
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Mat3 R;
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@ -764,7 +764,7 @@ inline void SVD::solveZ( InputArray m, OutputArray _dst )
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template<typename _Tp, int m, int n, int nm> inline void
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SVD::compute( const Matx<_Tp, m, n>& a, Matx<_Tp, nm, 1>& w, Matx<_Tp, m, nm>& u, Matx<_Tp, n, nm>& vt )
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{
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assert( nm == MIN(m, n));
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CV_StaticAssert( nm == MIN(m, n), "Invalid size of output vector.");
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Mat _a(a, false), _u(u, false), _w(w, false), _vt(vt, false);
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SVD::compute(_a, _w, _u, _vt);
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CV_Assert(_w.data == (uchar*)&w.val[0] && _u.data == (uchar*)&u.val[0] && _vt.data == (uchar*)&vt.val[0]);
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@ -773,7 +773,7 @@ template<typename _Tp, int m, int n, int nm> inline void
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template<typename _Tp, int m, int n, int nm> inline void
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SVD::compute( const Matx<_Tp, m, n>& a, Matx<_Tp, nm, 1>& w )
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{
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assert( nm == MIN(m, n));
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CV_StaticAssert( nm == MIN(m, n), "Invalid size of output vector.");
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Mat _a(a, false), _w(w, false);
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SVD::compute(_a, _w);
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CV_Assert(_w.data == (uchar*)&w.val[0]);
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@ -784,7 +784,7 @@ SVD::backSubst( const Matx<_Tp, nm, 1>& w, const Matx<_Tp, m, nm>& u,
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const Matx<_Tp, n, nm>& vt, const Matx<_Tp, m, nb>& rhs,
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Matx<_Tp, n, nb>& dst )
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{
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assert( nm == MIN(m, n));
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CV_StaticAssert( nm == MIN(m, n), "Invalid size of output vector.");
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Mat _u(u, false), _w(w, false), _vt(vt, false), _rhs(rhs, false), _dst(dst, false);
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SVD::backSubst(_w, _u, _vt, _rhs, _dst);
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CV_Assert(_dst.data == (uchar*)&dst.val[0]);
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@ -82,7 +82,7 @@
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# endif
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# ifndef CV_StaticAssert
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# if defined(__GNUC__) && (__GNUC__ > 3) && (__GNUC_MINOR__ > 2)
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# define CV_StaticAssert(condition, reason) ({ extern int __attribute__((error("CV_StaticAssert: " reason " " #condition))) CV_StaticAssert(); ((condition) ? 0 : CV_StaticAssert()), 0; })
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# define CV_StaticAssert(condition, reason) ({ extern int __attribute__((error("CV_StaticAssert: " reason " " #condition))) CV_StaticAssert(); ((condition) ? 0 : CV_StaticAssert()); })
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# else
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namespace cv {
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template <bool x> struct CV_StaticAssert_failed;
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@ -201,28 +201,28 @@ template<typename _Tp, int m, int n> inline Matx<_Tp, m, n>::Matx(_Tp v0)
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template<typename _Tp, int m, int n> inline Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1)
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{
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assert(channels >= 2);
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CV_StaticAssert(channels >= 2, "Matx should have at least 2 elaments.");
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val[0] = v0; val[1] = v1;
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for(int i = 2; i < channels; i++) val[i] = _Tp(0);
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}
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template<typename _Tp, int m, int n> inline Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1, _Tp v2)
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{
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assert(channels >= 3);
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CV_StaticAssert(channels >= 3, "Matx should have at least 3 elaments.");
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val[0] = v0; val[1] = v1; val[2] = v2;
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for(int i = 3; i < channels; i++) val[i] = _Tp(0);
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}
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template<typename _Tp, int m, int n> inline Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3)
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{
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assert(channels >= 4);
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CV_StaticAssert(channels >= 4, "Matx should have at least 4 elaments.");
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val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3;
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for(int i = 4; i < channels; i++) val[i] = _Tp(0);
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}
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template<typename _Tp, int m, int n> inline Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4)
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{
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assert(channels >= 5);
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CV_StaticAssert(channels >= 5, "Matx should have at least 5 elaments.");
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val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3; val[4] = v4;
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for(int i = 5; i < channels; i++) val[i] = _Tp(0);
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}
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@ -230,7 +230,7 @@ template<typename _Tp, int m, int n> inline Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1
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template<typename _Tp, int m, int n> inline Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3,
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_Tp v4, _Tp v5)
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{
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assert(channels >= 6);
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CV_StaticAssert(channels >= 6, "Matx should have at least 6 elaments.");
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val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3;
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val[4] = v4; val[5] = v5;
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for(int i = 6; i < channels; i++) val[i] = _Tp(0);
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@ -239,7 +239,7 @@ template<typename _Tp, int m, int n> inline Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1
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template<typename _Tp, int m, int n> inline Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3,
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_Tp v4, _Tp v5, _Tp v6)
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{
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assert(channels >= 7);
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CV_StaticAssert(channels >= 7, "Matx should have at least 7 elaments.");
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val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3;
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val[4] = v4; val[5] = v5; val[6] = v6;
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for(int i = 7; i < channels; i++) val[i] = _Tp(0);
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@ -248,7 +248,7 @@ template<typename _Tp, int m, int n> inline Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1
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template<typename _Tp, int m, int n> inline Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3,
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_Tp v4, _Tp v5, _Tp v6, _Tp v7)
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{
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assert(channels >= 8);
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CV_StaticAssert(channels >= 8, "Matx should have at least 8 elaments.");
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val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3;
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val[4] = v4; val[5] = v5; val[6] = v6; val[7] = v7;
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for(int i = 8; i < channels; i++) val[i] = _Tp(0);
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@ -258,7 +258,7 @@ template<typename _Tp, int m, int n> inline Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1
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_Tp v4, _Tp v5, _Tp v6, _Tp v7,
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_Tp v8)
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{
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assert(channels >= 9);
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CV_StaticAssert(channels >= 9, "Matx should have at least 9 elaments.");
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val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3;
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val[4] = v4; val[5] = v5; val[6] = v6; val[7] = v7;
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val[8] = v8;
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@ -269,7 +269,7 @@ template<typename _Tp, int m, int n> inline Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1
|
||||
_Tp v4, _Tp v5, _Tp v6, _Tp v7,
|
||||
_Tp v8, _Tp v9)
|
||||
{
|
||||
assert(channels >= 10);
|
||||
CV_StaticAssert(channels >= 10, "Matx should have at least 10 elaments.");
|
||||
val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3;
|
||||
val[4] = v4; val[5] = v5; val[6] = v6; val[7] = v7;
|
||||
val[8] = v8; val[9] = v9;
|
||||
@ -282,7 +282,7 @@ inline Matx<_Tp,m,n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3,
|
||||
_Tp v4, _Tp v5, _Tp v6, _Tp v7,
|
||||
_Tp v8, _Tp v9, _Tp v10, _Tp v11)
|
||||
{
|
||||
assert(channels == 12);
|
||||
CV_StaticAssert(channels == 12, "Matx should have at least 12 elaments.");
|
||||
val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3;
|
||||
val[4] = v4; val[5] = v5; val[6] = v6; val[7] = v7;
|
||||
val[8] = v8; val[9] = v9; val[10] = v10; val[11] = v11;
|
||||
@ -294,7 +294,7 @@ inline Matx<_Tp,m,n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3,
|
||||
_Tp v8, _Tp v9, _Tp v10, _Tp v11,
|
||||
_Tp v12, _Tp v13, _Tp v14, _Tp v15)
|
||||
{
|
||||
assert(channels == 16);
|
||||
CV_StaticAssert(channels == 16, "Matx should have at least 16 elaments.");
|
||||
val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3;
|
||||
val[4] = v4; val[5] = v5; val[6] = v6; val[7] = v7;
|
||||
val[8] = v8; val[9] = v9; val[10] = v10; val[11] = v11;
|
||||
|
||||
@ -100,61 +100,61 @@ void FAST_t(InputArray _img, std::vector<KeyPoint>& keypoints, int threshold, bo
|
||||
#if CV_SSE2
|
||||
if( patternSize == 16 )
|
||||
{
|
||||
for(; j < img.cols - 16 - 3; j += 16, ptr += 16)
|
||||
{
|
||||
__m128i m0, m1;
|
||||
__m128i v0 = _mm_loadu_si128((const __m128i*)ptr);
|
||||
__m128i v1 = _mm_xor_si128(_mm_subs_epu8(v0, t), delta);
|
||||
v0 = _mm_xor_si128(_mm_adds_epu8(v0, t), delta);
|
||||
|
||||
__m128i x0 = _mm_sub_epi8(_mm_loadu_si128((const __m128i*)(ptr + pixel[0])), delta);
|
||||
__m128i x1 = _mm_sub_epi8(_mm_loadu_si128((const __m128i*)(ptr + pixel[quarterPatternSize])), delta);
|
||||
__m128i x2 = _mm_sub_epi8(_mm_loadu_si128((const __m128i*)(ptr + pixel[2*quarterPatternSize])), delta);
|
||||
__m128i x3 = _mm_sub_epi8(_mm_loadu_si128((const __m128i*)(ptr + pixel[3*quarterPatternSize])), delta);
|
||||
m0 = _mm_and_si128(_mm_cmpgt_epi8(x0, v0), _mm_cmpgt_epi8(x1, v0));
|
||||
m1 = _mm_and_si128(_mm_cmpgt_epi8(v1, x0), _mm_cmpgt_epi8(v1, x1));
|
||||
m0 = _mm_or_si128(m0, _mm_and_si128(_mm_cmpgt_epi8(x1, v0), _mm_cmpgt_epi8(x2, v0)));
|
||||
m1 = _mm_or_si128(m1, _mm_and_si128(_mm_cmpgt_epi8(v1, x1), _mm_cmpgt_epi8(v1, x2)));
|
||||
m0 = _mm_or_si128(m0, _mm_and_si128(_mm_cmpgt_epi8(x2, v0), _mm_cmpgt_epi8(x3, v0)));
|
||||
m1 = _mm_or_si128(m1, _mm_and_si128(_mm_cmpgt_epi8(v1, x2), _mm_cmpgt_epi8(v1, x3)));
|
||||
m0 = _mm_or_si128(m0, _mm_and_si128(_mm_cmpgt_epi8(x3, v0), _mm_cmpgt_epi8(x0, v0)));
|
||||
m1 = _mm_or_si128(m1, _mm_and_si128(_mm_cmpgt_epi8(v1, x3), _mm_cmpgt_epi8(v1, x0)));
|
||||
m0 = _mm_or_si128(m0, m1);
|
||||
int mask = _mm_movemask_epi8(m0);
|
||||
if( mask == 0 )
|
||||
continue;
|
||||
if( (mask & 255) == 0 )
|
||||
for(; j < img.cols - 16 - 3; j += 16, ptr += 16)
|
||||
{
|
||||
j -= 8;
|
||||
ptr -= 8;
|
||||
continue;
|
||||
}
|
||||
__m128i m0, m1;
|
||||
__m128i v0 = _mm_loadu_si128((const __m128i*)ptr);
|
||||
__m128i v1 = _mm_xor_si128(_mm_subs_epu8(v0, t), delta);
|
||||
v0 = _mm_xor_si128(_mm_adds_epu8(v0, t), delta);
|
||||
|
||||
__m128i c0 = _mm_setzero_si128(), c1 = c0, max0 = c0, max1 = c0;
|
||||
for( k = 0; k < N; k++ )
|
||||
{
|
||||
__m128i x = _mm_xor_si128(_mm_loadu_si128((const __m128i*)(ptr + pixel[k])), delta);
|
||||
m0 = _mm_cmpgt_epi8(x, v0);
|
||||
m1 = _mm_cmpgt_epi8(v1, x);
|
||||
|
||||
c0 = _mm_and_si128(_mm_sub_epi8(c0, m0), m0);
|
||||
c1 = _mm_and_si128(_mm_sub_epi8(c1, m1), m1);
|
||||
|
||||
max0 = _mm_max_epu8(max0, c0);
|
||||
max1 = _mm_max_epu8(max1, c1);
|
||||
}
|
||||
|
||||
max0 = _mm_max_epu8(max0, max1);
|
||||
int m = _mm_movemask_epi8(_mm_cmpgt_epi8(max0, K16));
|
||||
|
||||
for( k = 0; m > 0 && k < 16; k++, m >>= 1 )
|
||||
if(m & 1)
|
||||
__m128i x0 = _mm_sub_epi8(_mm_loadu_si128((const __m128i*)(ptr + pixel[0])), delta);
|
||||
__m128i x1 = _mm_sub_epi8(_mm_loadu_si128((const __m128i*)(ptr + pixel[quarterPatternSize])), delta);
|
||||
__m128i x2 = _mm_sub_epi8(_mm_loadu_si128((const __m128i*)(ptr + pixel[2*quarterPatternSize])), delta);
|
||||
__m128i x3 = _mm_sub_epi8(_mm_loadu_si128((const __m128i*)(ptr + pixel[3*quarterPatternSize])), delta);
|
||||
m0 = _mm_and_si128(_mm_cmpgt_epi8(x0, v0), _mm_cmpgt_epi8(x1, v0));
|
||||
m1 = _mm_and_si128(_mm_cmpgt_epi8(v1, x0), _mm_cmpgt_epi8(v1, x1));
|
||||
m0 = _mm_or_si128(m0, _mm_and_si128(_mm_cmpgt_epi8(x1, v0), _mm_cmpgt_epi8(x2, v0)));
|
||||
m1 = _mm_or_si128(m1, _mm_and_si128(_mm_cmpgt_epi8(v1, x1), _mm_cmpgt_epi8(v1, x2)));
|
||||
m0 = _mm_or_si128(m0, _mm_and_si128(_mm_cmpgt_epi8(x2, v0), _mm_cmpgt_epi8(x3, v0)));
|
||||
m1 = _mm_or_si128(m1, _mm_and_si128(_mm_cmpgt_epi8(v1, x2), _mm_cmpgt_epi8(v1, x3)));
|
||||
m0 = _mm_or_si128(m0, _mm_and_si128(_mm_cmpgt_epi8(x3, v0), _mm_cmpgt_epi8(x0, v0)));
|
||||
m1 = _mm_or_si128(m1, _mm_and_si128(_mm_cmpgt_epi8(v1, x3), _mm_cmpgt_epi8(v1, x0)));
|
||||
m0 = _mm_or_si128(m0, m1);
|
||||
int mask = _mm_movemask_epi8(m0);
|
||||
if( mask == 0 )
|
||||
continue;
|
||||
if( (mask & 255) == 0 )
|
||||
{
|
||||
cornerpos[ncorners++] = j+k;
|
||||
if(nonmax_suppression)
|
||||
curr[j+k] = (uchar)cornerScore<patternSize>(ptr+k, pixel, threshold);
|
||||
j -= 8;
|
||||
ptr -= 8;
|
||||
continue;
|
||||
}
|
||||
}
|
||||
|
||||
__m128i c0 = _mm_setzero_si128(), c1 = c0, max0 = c0, max1 = c0;
|
||||
for( k = 0; k < N; k++ )
|
||||
{
|
||||
__m128i x = _mm_xor_si128(_mm_loadu_si128((const __m128i*)(ptr + pixel[k])), delta);
|
||||
m0 = _mm_cmpgt_epi8(x, v0);
|
||||
m1 = _mm_cmpgt_epi8(v1, x);
|
||||
|
||||
c0 = _mm_and_si128(_mm_sub_epi8(c0, m0), m0);
|
||||
c1 = _mm_and_si128(_mm_sub_epi8(c1, m1), m1);
|
||||
|
||||
max0 = _mm_max_epu8(max0, c0);
|
||||
max1 = _mm_max_epu8(max1, c1);
|
||||
}
|
||||
|
||||
max0 = _mm_max_epu8(max0, max1);
|
||||
int m = _mm_movemask_epi8(_mm_cmpgt_epi8(max0, K16));
|
||||
|
||||
for( k = 0; m > 0 && k < 16; k++, m >>= 1 )
|
||||
if(m & 1)
|
||||
{
|
||||
cornerpos[ncorners++] = j+k;
|
||||
if(nonmax_suppression)
|
||||
curr[j+k] = (uchar)cornerScore<patternSize>(ptr+k, pixel, threshold);
|
||||
}
|
||||
}
|
||||
}
|
||||
#endif
|
||||
for( ; j < img.cols - 3; j++, ptr++ )
|
||||
|
||||
@ -208,7 +208,6 @@ private:
|
||||
#define SANITY_CHECK_KEYPOINTS(array, ...) ::perf::Regression::addKeypoints(this, #array, array , ## __VA_ARGS__)
|
||||
#define SANITY_CHECK_MATCHES(array, ...) ::perf::Regression::addMatches(this, #array, array , ## __VA_ARGS__)
|
||||
|
||||
#ifdef HAVE_CUDA
|
||||
class CV_EXPORTS GpuPerf
|
||||
{
|
||||
public:
|
||||
@ -216,9 +215,6 @@ public:
|
||||
};
|
||||
|
||||
# define PERF_RUN_GPU() ::perf::GpuPerf::targetDevice()
|
||||
#else
|
||||
# define PERF_RUN_GPU() false
|
||||
#endif
|
||||
|
||||
|
||||
/*****************************************************************************************\
|
||||
|
||||
@ -1324,12 +1324,14 @@ void perf::sort(std::vector<cv::KeyPoint>& pts, cv::InputOutputArray descriptors
|
||||
/*****************************************************************************************\
|
||||
* ::perf::GpuPerf
|
||||
\*****************************************************************************************/
|
||||
#ifdef HAVE_CUDA
|
||||
bool perf::GpuPerf::targetDevice()
|
||||
{
|
||||
#ifdef HAVE_CUDA
|
||||
return !param_run_cpu;
|
||||
}
|
||||
#else
|
||||
return false;
|
||||
#endif
|
||||
}
|
||||
|
||||
/*****************************************************************************************\
|
||||
* ::perf::PrintTo
|
||||
|
||||
Loading…
Reference in New Issue
Block a user