#define CHECK_C
-class Core_PCATest : public cvtest::BaseTest
+TEST(Core_PCA, accuracy)
{
-public:
- Core_PCATest() {}
-protected:
- void run(int)
- {
- const Size sz(200, 500);
-
- double diffPrjEps, diffBackPrjEps,
- prjEps, backPrjEps,
- evalEps, evecEps;
- int maxComponents = 100;
- double retainedVariance = 0.95;
- Mat rPoints(sz, CV_32FC1), rTestPoints(sz, CV_32FC1);
- RNG& rng = ts->get_rng();
-
- rng.fill( rPoints, RNG::UNIFORM, Scalar::all(0.0), Scalar::all(1.0) );
- rng.fill( rTestPoints, RNG::UNIFORM, Scalar::all(0.0), Scalar::all(1.0) );
-
- PCA rPCA( rPoints, Mat(), CV_PCA_DATA_AS_ROW, maxComponents ), cPCA;
-
- // 1. check C++ PCA & ROW
- Mat rPrjTestPoints = rPCA.project( rTestPoints );
- Mat rBackPrjTestPoints = rPCA.backProject( rPrjTestPoints );
-
- Mat avg(1, sz.width, CV_32FC1 );
- cv::reduce( rPoints, avg, 0, CV_REDUCE_AVG );
- Mat Q = rPoints - repeat( avg, rPoints.rows, 1 ), Qt = Q.t(), eval, evec;
- Q = Qt * Q;
- Q = Q /(float)rPoints.rows;
-
- eigen( Q, eval, evec );
- /*SVD svd(Q);
- evec = svd.vt;
- eval = svd.w;*/
-
- Mat subEval( maxComponents, 1, eval.type(), eval.ptr() ),
- subEvec( maxComponents, evec.cols, evec.type(), evec.ptr() );
-
- #ifdef CHECK_C
- Mat prjTestPoints, backPrjTestPoints, cPoints = rPoints.t(), cTestPoints = rTestPoints.t();
- CvMat _points, _testPoints, _avg, _eval, _evec, _prjTestPoints, _backPrjTestPoints;
- #endif
-
- // check eigen()
- double eigenEps = 1e-6;
- double err;
- for(int i = 0; i < Q.rows; i++ )
- {
- Mat v = evec.row(i).t();
- Mat Qv = Q * v;
-
- Mat lv = eval.at<float>(i,0) * v;
- err = cvtest::norm( Qv, lv, NORM_L2 );
- if( err > eigenEps )
- {
- ts->printf( cvtest::TS::LOG, "bad accuracy of eigen(); err = %f\n", err );
- ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
- return;
- }
- }
- // check pca eigenvalues
- evalEps = 1e-6, evecEps = 1e-3;
- err = cvtest::norm( rPCA.eigenvalues, subEval, NORM_L2 );
- if( err > evalEps )
- {
- ts->printf( cvtest::TS::LOG, "pca.eigenvalues is incorrect (CV_PCA_DATA_AS_ROW); err = %f\n", err );
- ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
- return;
- }
- // check pca eigenvectors
- for(int i = 0; i < subEvec.rows; i++)
- {
- Mat r0 = rPCA.eigenvectors.row(i);
- Mat r1 = subEvec.row(i);
- err = cvtest::norm( r0, r1, CV_L2 );
- if( err > evecEps )
- {
- r1 *= -1;
- double err2 = cvtest::norm(r0, r1, CV_L2);
- if( err2 > evecEps )
- {
- Mat tmp;
- absdiff(rPCA.eigenvectors, subEvec, tmp);
- double mval = 0; Point mloc;
- minMaxLoc(tmp, 0, &mval, 0, &mloc);
-
- ts->printf( cvtest::TS::LOG, "pca.eigenvectors is incorrect (CV_PCA_DATA_AS_ROW); err = %f\n", err );
- ts->printf( cvtest::TS::LOG, "max diff is %g at (i=%d, j=%d) (%g vs %g)\n",
- mval, mloc.y, mloc.x, rPCA.eigenvectors.at<float>(mloc.y, mloc.x),
- subEvec.at<float>(mloc.y, mloc.x));
- ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
- return;
- }
- }
- }
-
- prjEps = 1.265, backPrjEps = 1.265;
- for( int i = 0; i < rTestPoints.rows; i++ )
- {
- // check pca project
- Mat subEvec_t = subEvec.t();
- Mat prj = rTestPoints.row(i) - avg; prj *= subEvec_t;
- err = cvtest::norm(rPrjTestPoints.row(i), prj, CV_RELATIVE_L2);
- if( err > prjEps )
- {
- ts->printf( cvtest::TS::LOG, "bad accuracy of project() (CV_PCA_DATA_AS_ROW); err = %f\n", err );
- ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
- return;
- }
- // check pca backProject
- Mat backPrj = rPrjTestPoints.row(i) * subEvec + avg;
- err = cvtest::norm( rBackPrjTestPoints.row(i), backPrj, CV_RELATIVE_L2 );
- if( err > backPrjEps )
- {
- ts->printf( cvtest::TS::LOG, "bad accuracy of backProject() (CV_PCA_DATA_AS_ROW); err = %f\n", err );
- ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
- return;
- }
- }
-
- // 2. check C++ PCA & COL
- cPCA( rPoints.t(), Mat(), CV_PCA_DATA_AS_COL, maxComponents );
- diffPrjEps = 1, diffBackPrjEps = 1;
- Mat ocvPrjTestPoints = cPCA.project(rTestPoints.t());
- err = cvtest::norm(cv::abs(ocvPrjTestPoints), cv::abs(rPrjTestPoints.t()), CV_RELATIVE_L2 );
- if( err > diffPrjEps )
- {
- ts->printf( cvtest::TS::LOG, "bad accuracy of project() (CV_PCA_DATA_AS_COL); err = %f\n", err );
- ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
- return;
- }
- err = cvtest::norm(cPCA.backProject(ocvPrjTestPoints), rBackPrjTestPoints.t(), CV_RELATIVE_L2 );
- if( err > diffBackPrjEps )
- {
- ts->printf( cvtest::TS::LOG, "bad accuracy of backProject() (CV_PCA_DATA_AS_COL); err = %f\n", err );
- ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
- return;
- }
-
- // 3. check C++ PCA w/retainedVariance
- cPCA( rPoints.t(), Mat(), CV_PCA_DATA_AS_COL, retainedVariance );
- diffPrjEps = 1, diffBackPrjEps = 1;
- Mat rvPrjTestPoints = cPCA.project(rTestPoints.t());
-
- if( cPCA.eigenvectors.rows > maxComponents)
- err = cvtest::norm(cv::abs(rvPrjTestPoints.rowRange(0,maxComponents)), cv::abs(rPrjTestPoints.t()), CV_RELATIVE_L2 );
- else
- err = cvtest::norm(cv::abs(rvPrjTestPoints), cv::abs(rPrjTestPoints.colRange(0,cPCA.eigenvectors.rows).t()), CV_RELATIVE_L2 );
+ const Size sz(200, 500);
+
+ double diffPrjEps, diffBackPrjEps,
+ prjEps, backPrjEps,
+ evalEps, evecEps;
+ int maxComponents = 100;
+ double retainedVariance = 0.95;
+ Mat rPoints(sz, CV_32FC1), rTestPoints(sz, CV_32FC1);
+ RNG rng(12345);
+
+ rng.fill( rPoints, RNG::UNIFORM, Scalar::all(0.0), Scalar::all(1.0) );
+ rng.fill( rTestPoints, RNG::UNIFORM, Scalar::all(0.0), Scalar::all(1.0) );
+
+ PCA rPCA( rPoints, Mat(), CV_PCA_DATA_AS_ROW, maxComponents ), cPCA;
+
+ // 1. check C++ PCA & ROW
+ Mat rPrjTestPoints = rPCA.project( rTestPoints );
+ Mat rBackPrjTestPoints = rPCA.backProject( rPrjTestPoints );
+
+ Mat avg(1, sz.width, CV_32FC1 );
+ cv::reduce( rPoints, avg, 0, CV_REDUCE_AVG );
+ Mat Q = rPoints - repeat( avg, rPoints.rows, 1 ), Qt = Q.t(), eval, evec;
+ Q = Qt * Q;
+ Q = Q /(float)rPoints.rows;
+
+ eigen( Q, eval, evec );
+ /*SVD svd(Q);
+ evec = svd.vt;
+ eval = svd.w;*/
+
+ Mat subEval( maxComponents, 1, eval.type(), eval.ptr() ),
+ subEvec( maxComponents, evec.cols, evec.type(), evec.ptr() );
+
+#ifdef CHECK_C
+ Mat prjTestPoints, backPrjTestPoints, cPoints = rPoints.t(), cTestPoints = rTestPoints.t();
+ CvMat _points, _testPoints, _avg, _eval, _evec, _prjTestPoints, _backPrjTestPoints;
+#endif
- if( err > diffPrjEps )
- {
- ts->printf( cvtest::TS::LOG, "bad accuracy of project() (CV_PCA_DATA_AS_COL); retainedVariance=0.95; err = %f\n", err );
- ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
- return;
- }
- err = cvtest::norm(cPCA.backProject(rvPrjTestPoints), rBackPrjTestPoints.t(), CV_RELATIVE_L2 );
- if( err > diffBackPrjEps )
- {
- ts->printf( cvtest::TS::LOG, "bad accuracy of backProject() (CV_PCA_DATA_AS_COL); retainedVariance=0.95; err = %f\n", err );
- ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
- return;
- }
+ // check eigen()
+ double eigenEps = 1e-4;
+ double err;
+ for(int i = 0; i < Q.rows; i++ )
+ {
+ Mat v = evec.row(i).t();
+ Mat Qv = Q * v;
- #ifdef CHECK_C
- // 4. check C PCA & ROW
- _points = rPoints;
- _testPoints = rTestPoints;
- _avg = avg;
- _eval = eval;
- _evec = evec;
- prjTestPoints.create(rTestPoints.rows, maxComponents, rTestPoints.type() );
- backPrjTestPoints.create(rPoints.size(), rPoints.type() );
- _prjTestPoints = prjTestPoints;
- _backPrjTestPoints = backPrjTestPoints;
-
- cvCalcPCA( &_points, &_avg, &_eval, &_evec, CV_PCA_DATA_AS_ROW );
- cvProjectPCA( &_testPoints, &_avg, &_evec, &_prjTestPoints );
- cvBackProjectPCA( &_prjTestPoints, &_avg, &_evec, &_backPrjTestPoints );
-
- err = cvtest::norm(prjTestPoints, rPrjTestPoints, CV_RELATIVE_L2);
- if( err > diffPrjEps )
- {
- ts->printf( cvtest::TS::LOG, "bad accuracy of cvProjectPCA() (CV_PCA_DATA_AS_ROW); err = %f\n", err );
- ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
- return;
- }
- err = cvtest::norm(backPrjTestPoints, rBackPrjTestPoints, CV_RELATIVE_L2);
- if( err > diffBackPrjEps )
+ Mat lv = eval.at<float>(i,0) * v;
+ err = cvtest::norm(Qv, lv, NORM_L2 | NORM_RELATIVE);
+ EXPECT_LE(err, eigenEps) << "bad accuracy of eigen(); i = " << i;
+ }
+ // check pca eigenvalues
+ evalEps = 1e-5, evecEps = 5e-3;
+ err = cvtest::norm(rPCA.eigenvalues, subEval, NORM_L2 | NORM_RELATIVE);
+ EXPECT_LE(err , evalEps) << "pca.eigenvalues is incorrect (CV_PCA_DATA_AS_ROW)";
+ // check pca eigenvectors
+ for(int i = 0; i < subEvec.rows; i++)
+ {
+ Mat r0 = rPCA.eigenvectors.row(i);
+ Mat r1 = subEvec.row(i);
+ // eigenvectors have normalized length, but both directions v and -v are valid
+ double err1 = cvtest::norm(r0, r1, NORM_L2 | NORM_RELATIVE);
+ double err2 = cvtest::norm(r0, -r1, NORM_L2 | NORM_RELATIVE);
+ err = std::min(err1, err2);
+ if (err > evecEps)
{
- ts->printf( cvtest::TS::LOG, "bad accuracy of cvBackProjectPCA() (CV_PCA_DATA_AS_ROW); err = %f\n", err );
- ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
- return;
+ Mat tmp;
+ absdiff(rPCA.eigenvectors, subEvec, tmp);
+ double mval = 0; Point mloc;
+ minMaxLoc(tmp, 0, &mval, 0, &mloc);
+
+ EXPECT_LE(err, evecEps) << "pca.eigenvectors is incorrect (CV_PCA_DATA_AS_ROW) at " << i << " "
+ << cv::format("max diff is %g at (i=%d, j=%d) (%g vs %g)\n",
+ mval, mloc.y, mloc.x, rPCA.eigenvectors.at<float>(mloc.y, mloc.x),
+ subEvec.at<float>(mloc.y, mloc.x))
+ << "r0=" << r0 << std::endl
+ << "r1=" << r1 << std::endl
+ << "err1=" << err1 << " err2=" << err2
+ ;
}
+ }
- // 5. check C PCA & COL
- _points = cPoints;
- _testPoints = cTestPoints;
- avg = avg.t(); _avg = avg;
- eval = eval.t(); _eval = eval;
- evec = evec.t(); _evec = evec;
- prjTestPoints = prjTestPoints.t(); _prjTestPoints = prjTestPoints;
- backPrjTestPoints = backPrjTestPoints.t(); _backPrjTestPoints = backPrjTestPoints;
-
- cvCalcPCA( &_points, &_avg, &_eval, &_evec, CV_PCA_DATA_AS_COL );
- cvProjectPCA( &_testPoints, &_avg, &_evec, &_prjTestPoints );
- cvBackProjectPCA( &_prjTestPoints, &_avg, &_evec, &_backPrjTestPoints );
-
- err = cvtest::norm(cv::abs(prjTestPoints), cv::abs(rPrjTestPoints.t()), CV_RELATIVE_L2 );
- if( err > diffPrjEps )
- {
- ts->printf( cvtest::TS::LOG, "bad accuracy of cvProjectPCA() (CV_PCA_DATA_AS_COL); err = %f\n", err );
- ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
- return;
- }
- err = cvtest::norm(backPrjTestPoints, rBackPrjTestPoints.t(), CV_RELATIVE_L2);
- if( err > diffBackPrjEps )
- {
- ts->printf( cvtest::TS::LOG, "bad accuracy of cvBackProjectPCA() (CV_PCA_DATA_AS_COL); err = %f\n", err );
- ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
- return;
- }
- #endif
- // Test read and write
- FileStorage fs( "PCA_store.yml", FileStorage::WRITE );
- rPCA.write( fs );
- fs.release();
-
- PCA lPCA;
- fs.open( "PCA_store.yml", FileStorage::READ );
- lPCA.read( fs.root() );
- err = cvtest::norm( rPCA.eigenvectors, lPCA.eigenvectors, CV_RELATIVE_L2 );
- if( err > 0 )
- {
- ts->printf( cvtest::TS::LOG, "bad accuracy of write/load functions (YML); err = %f\n", err );
- ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
- }
- err = cvtest::norm( rPCA.eigenvalues, lPCA.eigenvalues, CV_RELATIVE_L2 );
- if( err > 0 )
+ prjEps = 1.265, backPrjEps = 1.265;
+ for( int i = 0; i < rTestPoints.rows; i++ )
+ {
+ // check pca project
+ Mat subEvec_t = subEvec.t();
+ Mat prj = rTestPoints.row(i) - avg; prj *= subEvec_t;
+ err = cvtest::norm(rPrjTestPoints.row(i), prj, NORM_L2 | NORM_RELATIVE);
+ if (err < prjEps)
{
- ts->printf( cvtest::TS::LOG, "bad accuracy of write/load functions (YML); err = %f\n", err );
- ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
+ EXPECT_LE(err, prjEps) << "bad accuracy of project() (CV_PCA_DATA_AS_ROW)";
+ continue;
}
- err = cvtest::norm( rPCA.mean, lPCA.mean, CV_RELATIVE_L2 );
- if( err > 0 )
+ // check pca backProject
+ Mat backPrj = rPrjTestPoints.row(i) * subEvec + avg;
+ err = cvtest::norm(rBackPrjTestPoints.row(i), backPrj, NORM_L2 | NORM_RELATIVE);
+ if (err > backPrjEps)
{
- ts->printf( cvtest::TS::LOG, "bad accuracy of write/load functions (YML); err = %f\n", err );
- ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
+ EXPECT_LE(err, backPrjEps) << "bad accuracy of backProject() (CV_PCA_DATA_AS_ROW)";
+ continue;
}
}
-};
+
+ // 2. check C++ PCA & COL
+ cPCA( rPoints.t(), Mat(), CV_PCA_DATA_AS_COL, maxComponents );
+ diffPrjEps = 1, diffBackPrjEps = 1;
+ Mat ocvPrjTestPoints = cPCA.project(rTestPoints.t());
+ err = cvtest::norm(cv::abs(ocvPrjTestPoints), cv::abs(rPrjTestPoints.t()), NORM_L2 | NORM_RELATIVE);
+ ASSERT_LE(err, diffPrjEps) << "bad accuracy of project() (CV_PCA_DATA_AS_COL)";
+ err = cvtest::norm(cPCA.backProject(ocvPrjTestPoints), rBackPrjTestPoints.t(), NORM_L2 | NORM_RELATIVE);
+ ASSERT_LE(err, diffBackPrjEps) << "bad accuracy of backProject() (CV_PCA_DATA_AS_COL)";
+
+ // 3. check C++ PCA w/retainedVariance
+ cPCA( rPoints.t(), Mat(), CV_PCA_DATA_AS_COL, retainedVariance );
+ diffPrjEps = 1, diffBackPrjEps = 1;
+ Mat rvPrjTestPoints = cPCA.project(rTestPoints.t());
+
+ if( cPCA.eigenvectors.rows > maxComponents)
+ err = cvtest::norm(cv::abs(rvPrjTestPoints.rowRange(0,maxComponents)), cv::abs(rPrjTestPoints.t()), NORM_L2 | NORM_RELATIVE);
+ else
+ err = cvtest::norm(cv::abs(rvPrjTestPoints), cv::abs(rPrjTestPoints.colRange(0,cPCA.eigenvectors.rows).t()), NORM_L2 | NORM_RELATIVE);
+
+ ASSERT_LE(err, diffPrjEps) << "bad accuracy of project() (CV_PCA_DATA_AS_COL); retainedVariance=" << retainedVariance;
+ err = cvtest::norm(cPCA.backProject(rvPrjTestPoints), rBackPrjTestPoints.t(), NORM_L2 | NORM_RELATIVE);
+ ASSERT_LE(err, diffBackPrjEps) << "bad accuracy of backProject() (CV_PCA_DATA_AS_COL); retainedVariance=" << retainedVariance;
+
+#ifdef CHECK_C
+ // 4. check C PCA & ROW
+ _points = rPoints;
+ _testPoints = rTestPoints;
+ _avg = avg;
+ _eval = eval;
+ _evec = evec;
+ prjTestPoints.create(rTestPoints.rows, maxComponents, rTestPoints.type() );
+ backPrjTestPoints.create(rPoints.size(), rPoints.type() );
+ _prjTestPoints = prjTestPoints;
+ _backPrjTestPoints = backPrjTestPoints;
+
+ cvCalcPCA( &_points, &_avg, &_eval, &_evec, CV_PCA_DATA_AS_ROW );
+ cvProjectPCA( &_testPoints, &_avg, &_evec, &_prjTestPoints );
+ cvBackProjectPCA( &_prjTestPoints, &_avg, &_evec, &_backPrjTestPoints );
+
+ err = cvtest::norm(prjTestPoints, rPrjTestPoints, NORM_L2 | NORM_RELATIVE);
+ ASSERT_LE(err, diffPrjEps) << "bad accuracy of cvProjectPCA() (CV_PCA_DATA_AS_ROW)";
+ err = cvtest::norm(backPrjTestPoints, rBackPrjTestPoints, NORM_L2 | NORM_RELATIVE);
+ ASSERT_LE(err, diffBackPrjEps) << "bad accuracy of cvBackProjectPCA() (CV_PCA_DATA_AS_ROW)";
+
+ // 5. check C PCA & COL
+ _points = cPoints;
+ _testPoints = cTestPoints;
+ avg = avg.t(); _avg = avg;
+ eval = eval.t(); _eval = eval;
+ evec = evec.t(); _evec = evec;
+ prjTestPoints = prjTestPoints.t(); _prjTestPoints = prjTestPoints;
+ backPrjTestPoints = backPrjTestPoints.t(); _backPrjTestPoints = backPrjTestPoints;
+
+ cvCalcPCA( &_points, &_avg, &_eval, &_evec, CV_PCA_DATA_AS_COL );
+ cvProjectPCA( &_testPoints, &_avg, &_evec, &_prjTestPoints );
+ cvBackProjectPCA( &_prjTestPoints, &_avg, &_evec, &_backPrjTestPoints );
+
+ err = cvtest::norm(cv::abs(prjTestPoints), cv::abs(rPrjTestPoints.t()), NORM_L2 | NORM_RELATIVE);
+ ASSERT_LE(err, diffPrjEps) << "bad accuracy of cvProjectPCA() (CV_PCA_DATA_AS_COL)";
+ err = cvtest::norm(backPrjTestPoints, rBackPrjTestPoints.t(), NORM_L2 | NORM_RELATIVE);
+ ASSERT_LE(err, diffBackPrjEps) << "bad accuracy of cvBackProjectPCA() (CV_PCA_DATA_AS_COL)";
+#endif
+ // Test read and write
+ FileStorage fs( "PCA_store.yml", FileStorage::WRITE );
+ rPCA.write( fs );
+ fs.release();
+
+ PCA lPCA;
+ fs.open( "PCA_store.yml", FileStorage::READ );
+ lPCA.read( fs.root() );
+ err = cvtest::norm(rPCA.eigenvectors, lPCA.eigenvectors, NORM_L2 | NORM_RELATIVE);
+ EXPECT_LE(err, 0) << "bad accuracy of write/load functions (YML)";
+ err = cvtest::norm(rPCA.eigenvalues, lPCA.eigenvalues, NORM_L2 | NORM_RELATIVE);
+ EXPECT_LE(err, 0) << "bad accuracy of write/load functions (YML)";
+ err = cvtest::norm(rPCA.mean, lPCA.mean, NORM_L2 | NORM_RELATIVE);
+ EXPECT_LE(err, 0) << "bad accuracy of write/load functions (YML)";
+}
class Core_ArrayOpTest : public cvtest::BaseTest
{
}
};
-TEST(Core_PCA, accuracy) { Core_PCATest test; test.safe_run(); }
TEST(Core_Reduce, accuracy) { Core_ReduceTest test; test.safe_run(); }
TEST(Core_Array, basic_operations) { Core_ArrayOpTest test; test.safe_run(); }
projects / platform / upstream / opencv.git / commitdiff