}
double correctPerc = correctMatches / (double)pointsCount;
- if (correctPerc < .75)
- {
- ts->printf( cvtest::TS::LOG, "correct_perc = %d\n", correctPerc );
- code = cvtest::TS::FAIL_BAD_ACCURACY;
- }
+ EXPECT_GE(correctPerc, .75) << "correctMatches=" << correctMatches << " pointsCount=" << pointsCount;
}
return code;
releaseModel();
+ if (::testing::Test::HasFailure()) code = cvtest::TS::FAIL_BAD_ACCURACY;
ts->set_failed_test_info( code );
}
}
// compare results
- if( cvtest::norm( neighbors, neighbors1, NORM_L1 ) != 0 )
- return cvtest::TS::FAIL_BAD_ACCURACY;
+ EXPECT_LE(cvtest::norm(neighbors, neighbors1, NORM_L1), 0);
- return cvtest::TS::OK;
+ return ::testing::Test::HasFailure() ? cvtest::TS::FAIL_BAD_ACCURACY : cvtest::TS::OK;
}
int CV_FlannTest::radiusSearch( Mat& points, Mat& neighbors )
for( j = 0; it != indices.end(); ++it, j++ )
neighbors1.at<int>(i,j) = *it;
}
+
// compare results
- if( cvtest::norm( neighbors, neighbors1, NORM_L1 ) != 0 )
- return cvtest::TS::FAIL_BAD_ACCURACY;
+ EXPECT_LE(cvtest::norm(neighbors, neighbors1, NORM_L1), 0);
- return cvtest::TS::OK;
+ return ::testing::Test::HasFailure() ? cvtest::TS::FAIL_BAD_ACCURACY : cvtest::TS::OK;
}
void CV_FlannTest::releaseModel()