Merge pull request #5916 from berak:NormalBayesClassifier_bulk_prediction

modules/ml/src/nbayes.cpp

@@ -236,7 +236,7 @@ public:
             if (results_prob)
             {
                 rptype = results_prob->type();
-                rpstep = results_prob->isContinuous() ? 1 : results_prob->step/results_prob->elemSize();
+                rpstep = results_prob->isContinuous() ? results_prob->cols : results_prob->step/results_prob->elemSize();
             }
             // allocate memory and initializing headers for calculating
             cv::AutoBuffer<double> _buffer(nvars*2);

modules/ml/test/test_mltests.cpp

@@ -128,4 +128,48 @@ TEST(ML_Boost, regression) { CV_AMLTest test( CV_BOOST ); test.safe_run(); }
 TEST(ML_RTrees, regression) { CV_AMLTest test( CV_RTREES ); test.safe_run(); }
 TEST(DISABLED_ML_ERTrees, regression) { CV_AMLTest test( CV_ERTREES ); test.safe_run(); }
 
+TEST(ML_NBAYES, regression_5911)
+{
+    int N=12;
+    Ptr<ml::NormalBayesClassifier> nb = cv::ml::NormalBayesClassifier::create();
+
+    // data:
+    Mat_<float> X(N,4);
+    X << 1,2,3,4,  1,2,3,4,   1,2,3,4,    1,2,3,4,
+         5,5,5,5,  5,5,5,5,   5,5,5,5,    5,5,5,5,
+         4,3,2,1,  4,3,2,1,   4,3,2,1,    4,3,2,1;
+
+    // labels:
+    Mat_<int> Y(N,1);
+    Y << 0,0,0,0, 1,1,1,1, 2,2,2,2;
+    nb->train(X, ml::ROW_SAMPLE, Y);
+
+    // single prediction:
+    Mat R1,P1;
+    for (int i=0; i<N; i++)
+    {
+        Mat r,p;
+        nb->predictProb(X.row(i), r, p);
+        R1.push_back(r);
+        P1.push_back(p);
+    }
+
+    // bulk prediction (continuous memory):
+    Mat R2,P2;
+    nb->predictProb(X, R2, P2);
+
+    EXPECT_EQ(sum(R1 == R2)[0], 255 * R2.total());
+    EXPECT_EQ(sum(P1 == P2)[0], 255 * P2.total());
+
+    // bulk prediction, with non-continuous memory storage
+    Mat R3_(N, 1+1, CV_32S),
+        P3_(N, 3+1, CV_32F);
+    nb->predictProb(X, R3_.col(0), P3_.colRange(0,3));
+    Mat R3 = R3_.col(0).clone(),
+        P3 = P3_.colRange(0,3).clone();
+
+    EXPECT_EQ(sum(R1 == R3)[0], 255 * R3.total());
+    EXPECT_EQ(sum(P1 == P3)[0], 255 * P3.total());
+}
+
 /* End of file. */