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Merge pull request #19884 from danielenricocahall:fix-prediction-features-bug

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Fix bug with predictions in RTrees/Boost

* address bug where predict functions with invalid feature count in rtrees/boost models

* compact matrix rep in tests

* check 1..n-1 and n+1 in feature size validation test
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Danny 2021-04-09 12:56:14 -04:00 committed by GitHub
parent 76860933f0
commit a9a6801c6d
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3 changed files with 21 additions and 0 deletions
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1
modules/ml/src/boost.cpp
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@ -490,6 +490,7 @@ public:
float predict( InputArray samples, OutputArray results, int flags ) const CV_OVERRIDE
{
CV_Assert( samples.cols() == getVarCount() && samples.type() == CV_32F );
return impl.predict(samples, results, flags);
}

1
modules/ml/src/rtrees.cpp
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@ -479,6 +479,7 @@ public:
float predict( InputArray samples, OutputArray results, int flags ) const CV_OVERRIDE
{
CV_TRACE_FUNCTION();
CV_Assert( samples.cols() == getVarCount() && samples.type() == CV_32F );
return impl.predict(samples, results, flags);
}

19
modules/ml/test/test_rtrees.cpp
View File

@ -95,6 +95,25 @@ TEST(ML_RTrees, 11142_sample_weights_classification)
EXPECT_GE(error_with_weights, error_without_weights);
}
TEST(ML_RTrees, bug_12974_throw_exception_when_predict_different_feature_count)
{
int numFeatures = 5;
// create a 5 feature dataset and train the model
cv::Ptr<RTrees> model = RTrees::create();
Mat samples(10, numFeatures, CV_32F);
randu(samples, 0, 10);
Mat labels = (Mat_<int>(10,1) << 0,0,0,0,0,1,1,1,1,1);
cv::Ptr<TrainData> trainData = TrainData::create(samples, cv::ml::ROW_SAMPLE, labels);
model->train(trainData);
// try to predict on data which have fewer features - this should throw an exception
for(int i = 1; i < numFeatures - 1; ++i) {
Mat test(1, i, CV_32FC1);
ASSERT_THROW(model->predict(test), Exception);
}
// try to predict on data which have more features - this should also throw an exception
Mat test(1, numFeatures + 1, CV_32FC1);
ASSERT_THROW(model->predict(test), Exception);
}
}} // namespace