Merge pull request #6908 from ilya-lavrenov:reduce

modules/core/include/opencv2/core.hpp

@@ -826,9 +826,9 @@ CV_EXPORTS void minMaxLoc(const SparseMat& a, double* minVal,
 The function reduce reduces the matrix to a vector by treating the matrix rows/columns as a set of
 1D vectors and performing the specified operation on the vectors until a single row/column is
 obtained. For example, the function can be used to compute horizontal and vertical projections of a
-raster image. In case of REDUCE_SUM and REDUCE_AVG , the output may have a larger element
-bit-depth to preserve accuracy. And multi-channel arrays are also supported in these two reduction
-modes.
+raster image. In case of REDUCE_MAX and REDUCE_MIN , the output image should have the same type as the source one.
+In case of REDUCE_SUM and REDUCE_AVG , the output may have a larger element bit-depth to preserve accuracy.
+And multi-channel arrays are also supported in these two reduction modes.
 @param src input 2D matrix.
 @param dst output vector. Its size and type is defined by dim and dtype parameters.
 @param dim dimension index along which the matrix is reduced. 0 means that the matrix is reduced to

modules/core/test/test_mat.cpp

@@ -1509,3 +1509,14 @@ TEST(Mat, regression_6696_BigData_8Gb)
     EXPECT_EQ(4, destImageBGR.at<Vec4b>(height-1, width-1)[3]);
 }
 #endif
+
+TEST(Reduce, regression_should_fail_bug_4594)
+{
+    cv::Mat src = cv::Mat::eye(4, 4, CV_8U);
+    std::vector<int> dst;
+
+    EXPECT_THROW(cv::reduce(src, dst, 0, CV_REDUCE_MIN, CV_32S), cv::Exception);
+    EXPECT_THROW(cv::reduce(src, dst, 0, CV_REDUCE_MAX, CV_32S), cv::Exception);
+    EXPECT_NO_THROW(cv::reduce(src, dst, 0, CV_REDUCE_SUM, CV_32S));
+    EXPECT_NO_THROW(cv::reduce(src, dst, 0, CV_REDUCE_AVG, CV_32S));
+}