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ci fixes
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@@ -1427,8 +1427,8 @@ TEST_P(LandmarkCovarianceTest, LandmarkCovarianceAffectsConvergence)
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{
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const bool isG2O = (backend == Optimizer::kTypeG2O);
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landmarkDistMax = isG2O ? 0.15f : 0.05f; // g2o has no bearing-purity advantage
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poseDistMax = g2o6DoF ? 0.15f : 0.06f;
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poseAngMaxDeg = g2o6DoF ? 1.0f : 0.35f;
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poseDistMax = isG2O ? 0.20f : 0.06f;
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poseAngMaxDeg = isG2O ? 1.0f : 0.35f;
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}
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else if(noisy)
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{
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@@ -200,11 +200,16 @@ static Transform computeRegistrationRobust(
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RegistrationInfo * infoOut = nullptr)
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{
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const int estimationType = std::atoi(params.at(Parameters::kVisEstimationType()).c_str());
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const int maxAttempts = estimationType == 2 ? 20 : 1;
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const int maxAttempts = estimationType == 2 ? 50 : 1;
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Transform result;
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RegistrationInfo info;
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for(int attempt = 0; attempt < maxAttempts; ++attempt)
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{
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if(estimationType == 2)
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{
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cv::theRNG() = cv::RNG(static_cast<uint64_t>(0x9e3779b97f4a7c15ULL) ^
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static_cast<uint64_t>(attempt + 1));
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}
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result = computeRegistration(fromData, toData, params, &info);
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if(!result.isNull() || estimationType != 2)
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{
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@@ -2008,7 +2008,12 @@ TEST_F(RtabmapIntegrationFixture, AppearanceOnly_PrecisionRecall)
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<< ", FP=" << acceptedFp << ")\n";
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}
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const float recallFloor = (detectorType == defaultDetector) ? 0.5f : 0.9f;
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const bool isGfttBased =
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detectorType == Feature2D::kFeatureGfttFreak ||
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detectorType == Feature2D::kFeatureGfttBrief ||
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detectorType == Feature2D::kFeatureGfttOrb ||
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detectorType == Feature2D::kFeatureGfttDaisy;
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const float recallFloor = isGfttBased ? 0.5f : 0.9f;
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EXPECT_GE(recallAt100p, recallFloor)
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<< detectorLabel << " recall@100%P=" << recallAt100p
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<< " is below " << recallFloor
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