Merge remote-tracking branch 'upstream/3.4' into merge-3.4

modules/ml/src/data.cpp

@@ -43,6 +43,8 @@
 #include <algorithm>
 #include <iterator>
 
+#include <opencv2/core/utils/logger.hpp>
+
 namespace cv { namespace ml {
 
 static const float MISSED_VAL = TrainData::missingValue();
@@ -52,64 +54,60 @@ TrainData::~TrainData() {}
 
 Mat TrainData::getSubVector(const Mat& vec, const Mat& idx)
 {
-    if( idx.empty() )
-        return vec;
-    int i, j, n = idx.checkVector(1, CV_32S);
-    int type = vec.type();
-    CV_Assert( type == CV_32S || type == CV_32F || type == CV_64F );
-    int dims = 1, m;
+    if (!(vec.cols == 1 || vec.rows == 1))
+        CV_LOG_WARNING(NULL, "'getSubVector(const Mat& vec, const Mat& idx)' call with non-1D input is deprecated. It is not designed to work with 2D matrixes (especially with 'cv::ml::COL_SAMPLE' layout).");
+    return getSubMatrix(vec, idx, vec.rows == 1 ? cv::ml::COL_SAMPLE : cv::ml::ROW_SAMPLE);
+}
 
-    if( vec.cols == 1 || vec.rows == 1 )
+template<typename T>
+Mat getSubMatrixImpl(const Mat& m, const Mat& idx, int layout)
+{
+    int nidx = idx.checkVector(1, CV_32S);
+    int dims = m.cols, nsamples = m.rows;
+
+    Mat subm;
+    if (layout == COL_SAMPLE)
     {
-        dims = 1;
-        m = vec.cols + vec.rows - 1;
+        std::swap(dims, nsamples);
+        subm.create(dims, nidx, m.type());
     }
     else
     {
-        dims = vec.cols;
-        m = vec.rows;
+        subm.create(nidx, dims, m.type());
     }
 
-    Mat subvec;
+    for (int i = 0; i < nidx; i++)
+    {
+        int k = idx.at<int>(i); CV_CheckGE(k, 0, "Bad idx"); CV_CheckLT(k, nsamples, "Bad idx or layout");
+        if (dims == 1)
+        {
+            subm.at<T>(i) = m.at<T>(k);  // at() has "transparent" access for 1D col-based / row-based vectors.
+        }
+        else if (layout == COL_SAMPLE)
+        {
+            for (int j = 0; j < dims; j++)
+                subm.at<T>(j, i) = m.at<T>(j, k);
+        }
+        else
+        {
+            for (int j = 0; j < dims; j++)
+                subm.at<T>(i, j) = m.at<T>(k, j);
+        }
+    }
+    return subm;
+}
 
-    if( vec.cols == m )
-        subvec.create(dims, n, type);
-    else
-        subvec.create(n, dims, type);
-    if( type == CV_32S )
-        for( i = 0; i < n; i++ )
-        {
-            int k = idx.at<int>(i);
-            CV_Assert( 0 <= k && k < m );
-            if( dims == 1 )
-                subvec.at<int>(i) = vec.at<int>(k);
-            else
-                for( j = 0; j < dims; j++ )
-                    subvec.at<int>(i, j) = vec.at<int>(k, j);
-        }
-    else if( type == CV_32F )
-        for( i = 0; i < n; i++ )
-        {
-            int k = idx.at<int>(i);
-            CV_Assert( 0 <= k && k < m );
-            if( dims == 1 )
-                subvec.at<float>(i) = vec.at<float>(k);
-            else
-                for( j = 0; j < dims; j++ )
-                    subvec.at<float>(i, j) = vec.at<float>(k, j);
-        }
-    else
-        for( i = 0; i < n; i++ )
-        {
-            int k = idx.at<int>(i);
-            CV_Assert( 0 <= k && k < m );
-            if( dims == 1 )
-                subvec.at<double>(i) = vec.at<double>(k);
-            else
-                for( j = 0; j < dims; j++ )
-                    subvec.at<double>(i, j) = vec.at<double>(k, j);
-        }
-    return subvec;
+Mat TrainData::getSubMatrix(const Mat& m, const Mat& idx, int layout)
+{
+    if (idx.empty())
+        return m;
+    int type = m.type();
+    CV_CheckType(type, type == CV_32S || type == CV_32F || type == CV_64F, "");
+    if (type == CV_32S || type == CV_32F)  // 32-bit
+        return getSubMatrixImpl<int>(m, idx, layout);
+    if (type == CV_64F)  // 64-bit
+        return getSubMatrixImpl<double>(m, idx, layout);
+    CV_Error(Error::StsInternal, "");
 }
 
 
@@ -152,7 +150,7 @@ public:
     Mat getTestSamples() const CV_OVERRIDE
     {
         Mat idx = getTestSampleIdx();
-        return idx.empty() ? Mat() : getSubVector(samples, idx);
+        return idx.empty() ? Mat() : getSubMatrix(samples, idx, getLayout());
     }
 
     Mat getSamples() const CV_OVERRIDE { return samples; }
@@ -172,30 +170,30 @@ public:
     }
     Mat getTrainSampleWeights() const CV_OVERRIDE
     {
-        return getSubVector(sampleWeights, getTrainSampleIdx());
+        return getSubVector(sampleWeights, getTrainSampleIdx());  // 1D-vector
     }
     Mat getTestSampleWeights() const CV_OVERRIDE
     {
         Mat idx = getTestSampleIdx();
-        return idx.empty() ? Mat() : getSubVector(sampleWeights, idx);
+        return idx.empty() ? Mat() : getSubVector(sampleWeights, idx);  // 1D-vector
     }
     Mat getTrainResponses() const CV_OVERRIDE
     {
-        return getSubVector(responses, getTrainSampleIdx());
+        return getSubMatrix(responses, getTrainSampleIdx(), cv::ml::ROW_SAMPLE);  // col-based responses are transposed in setData()
     }
     Mat getTrainNormCatResponses() const CV_OVERRIDE
     {
-        return getSubVector(normCatResponses, getTrainSampleIdx());
+        return getSubMatrix(normCatResponses, getTrainSampleIdx(), cv::ml::ROW_SAMPLE);  // like 'responses'
     }
     Mat getTestResponses() const CV_OVERRIDE
     {
         Mat idx = getTestSampleIdx();
-        return idx.empty() ? Mat() : getSubVector(responses, idx);
+        return idx.empty() ? Mat() : getSubMatrix(responses, idx, cv::ml::ROW_SAMPLE);  // col-based responses are transposed in setData()
     }
     Mat getTestNormCatResponses() const CV_OVERRIDE
     {
         Mat idx = getTestSampleIdx();
-        return idx.empty() ? Mat() : getSubVector(normCatResponses, idx);
+        return idx.empty() ? Mat() : getSubMatrix(normCatResponses, idx, cv::ml::ROW_SAMPLE);  // like 'responses'
     }
     Mat getNormCatResponses() const CV_OVERRIDE { return normCatResponses; }
     Mat getClassLabels() const CV_OVERRIDE { return classLabels; }