opencv
diff --git a/‎modules/core/include/opencv2/core.hpp
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+3-2Lines changed: 3 additions & 2 deletions b/‎modules/core/include/opencv2/core.hpp
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+3-2Lines changed: 3 additions & 2 deletions
diff --git a/‎modules/core/perf/opencl/perf_arithm.cpp
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+2-3Lines changed: 2 additions & 3 deletions b/‎modules/core/perf/opencl/perf_arithm.cpp
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+2-3Lines changed: 2 additions & 3 deletions
diff --git a/‎modules/core/perf/perf_reduce.cpp
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+5-5Lines changed: 5 additions & 5 deletions b/‎modules/core/perf/perf_reduce.cpp
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+5-5Lines changed: 5 additions & 5 deletions
@@ -230,7 +230,8 @@ enum KmeansFlags {
 enum ReduceTypes { REDUCE_SUM = 0, //!< the output is the sum of all rows/columns of the matrix.
                    REDUCE_AVG = 1, //!< the output is the mean vector of all rows/columns of the matrix.
                    REDUCE_MAX = 2, //!< the output is the maximum (column/row-wise) of all rows/columns of the matrix.
-                   REDUCE_MIN = 3  //!< the output is the minimum (column/row-wise) of all rows/columns of the matrix.
+                   REDUCE_MIN = 3,  //!< the output is the minimum (column/row-wise) of all rows/columns of the matrix.
+                   REDUCE_SUM2 = 4  //!< the output is the sum of all squared rows/columns of the matrix.
                  };
 
 //! @} core_array
@@ -903,7 +904,7 @@ The function #reduce reduces the matrix to a vector by treating the matrix rows/
 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_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.
+In case of #REDUCE_SUM, #REDUCE_SUM2 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.
 
 The following code demonstrates its usage for a single channel matrix.
 
@@ -1150,7 +1150,7 @@ OCL_PERF_TEST_P(ReduceMinMaxFixture, Reduce,
     SANITY_CHECK(dst, eps);
 }
 
-CV_ENUM(ReduceAccOp, CV_REDUCE_SUM, CV_REDUCE_AVG)
+CV_ENUM(ReduceAccOp, REDUCE_SUM, REDUCE_AVG, REDUCE_SUM2)
 
 typedef tuple<Size, std::pair<MatType, MatType>, int, ReduceAccOp> ReduceAccParams;
 typedef TestBaseWithParam<ReduceAccParams> ReduceAccFixture;
@@ -1168,7 +1168,6 @@ OCL_PERF_TEST_P(ReduceAccFixture, Reduce,
             dim = get<2>(params), op = get<3>(params);
     const Size srcSize = get<0>(params),
             dstSize(dim == 0 ? srcSize.width : 1, dim == 0 ? 1 : srcSize.height);
-    const double eps = CV_MAT_DEPTH(dtype) <= CV_32S ? 1 : 3e-4;
 
     checkDeviceMaxMemoryAllocSize(srcSize, stype);
     checkDeviceMaxMemoryAllocSize(srcSize, dtype);
@@ -1178,7 +1177,7 @@ OCL_PERF_TEST_P(ReduceAccFixture, Reduce,
 
     OCL_TEST_CYCLE() cv::reduce(src, dst, dim, op, dtype);
 
-    SANITY_CHECK(dst, eps);
+    SANITY_CHECK_NOTHING();
 }
 
 } } // namespace opencv_test::ocl
 
@@ -5,7 +5,7 @@ namespace opencv_test
 {
 using namespace perf;
 
-CV_ENUM(ROp, CV_REDUCE_SUM, CV_REDUCE_AVG, CV_REDUCE_MAX, CV_REDUCE_MIN)
+CV_ENUM(ROp, REDUCE_SUM, REDUCE_AVG, REDUCE_MAX, REDUCE_MIN, REDUCE_SUM2)
 typedef tuple<Size, MatType, ROp> Size_MatType_ROp_t;
 typedef perf::TestBaseWithParam<Size_MatType_ROp_t> Size_MatType_ROp;
 
@@ -23,7 +23,7 @@ PERF_TEST_P(Size_MatType_ROp, reduceR,
     int reduceOp = get<2>(GetParam());
 
     int ddepth = -1;
-    if( CV_MAT_DEPTH(matType) < CV_32S && (reduceOp == REDUCE_SUM || reduceOp == REDUCE_AVG) )
+    if( CV_MAT_DEPTH(matType) < CV_32S && (reduceOp == REDUCE_SUM || reduceOp == REDUCE_AVG || reduceOp == REDUCE_SUM2) )
         ddepth = CV_32S;
 
     Mat src(sz, matType);
@@ -35,7 +35,7 @@ PERF_TEST_P(Size_MatType_ROp, reduceR,
     int runs = 15;
     TEST_CYCLE_MULTIRUN(runs) reduce(src, vec, 0, reduceOp, ddepth);
 
-    SANITY_CHECK(vec, 1);
+    SANITY_CHECK_NOTHING();
 }
 
 PERF_TEST_P(Size_MatType_ROp, reduceC,
@@ -51,7 +51,7 @@ PERF_TEST_P(Size_MatType_ROp, reduceC,
     int reduceOp = get<2>(GetParam());
 
     int ddepth = -1;
-    if( CV_MAT_DEPTH(matType)< CV_32S && (reduceOp == REDUCE_SUM || reduceOp == REDUCE_AVG) )
+    if( CV_MAT_DEPTH(matType)< CV_32S && (reduceOp == REDUCE_SUM || reduceOp == REDUCE_AVG || reduceOp == REDUCE_SUM2) )
         ddepth = CV_32S;
 
     Mat src(sz, matType);
@@ -62,7 +62,7 @@ PERF_TEST_P(Size_MatType_ROp, reduceC,
 
     TEST_CYCLE() reduce(src, vec, 1, reduceOp, ddepth);
 
-    SANITY_CHECK(vec, 1);
+    SANITY_CHECK_NOTHING();
 }
 
 typedef tuple<Size, MatType, int> Size_MatType_RMode_t;