Merge pull request #9208 from alalek:ipp_minmaxidx

modules/core/src/stat.cpp

@@ -2530,6 +2530,12 @@ static bool ipp_minMaxIdx(Mat &src, double* _minVal, double* _maxVal, int* _minI
         return false;
 #endif
 
+    // cv::minMaxIdx problem with index positions on AVX
+#if IPP_VERSION_X100 < 201810
+    if(!mask.empty() && _maxIdx && ipp::getIppFeatures()&ippCPUID_AVX)
+        return false;
+#endif
+
     IppStatus   status;
     IppDataType dataType = ippiGetDataType(src.depth());
     float       minVal = 0;
@@ -2561,7 +2567,7 @@ static bool ipp_minMaxIdx(Mat &src, double* _minVal, double* _maxVal, int* _minI
         size.width *= src.channels();
 
         status = ippMinMaxFun(src.ptr(), (int)src.step, size, dataType, pMinVal, pMaxVal, pMinIdx, pMaxIdx, (Ipp8u*)mask.ptr(), (int)mask.step);
-        if(status < 0 || status == ippStsNoOperation)
+        if(status < 0)
             return false;
         if(_minVal)
             *_minVal = minVal;
@@ -2569,7 +2575,8 @@ static bool ipp_minMaxIdx(Mat &src, double* _minVal, double* _maxVal, int* _minI
             *_maxVal = maxVal;
         if(_minIdx)
         {
-            if(!mask.empty() && !minIdx.y && !minIdx.x)
+            // Should be just ippStsNoOperation check, but there is a bug in the function so we need additional checks
+            if(status == ippStsNoOperation && !mask.empty() && !pMinIdx->x && !pMinIdx->y)
             {
                 _minIdx[0] = -1;
                 _minIdx[1] = -1;
@@ -2582,7 +2589,8 @@ static bool ipp_minMaxIdx(Mat &src, double* _minVal, double* _maxVal, int* _minI
         }
         if(_maxIdx)
         {
-            if(!mask.empty() && !maxIdx.y && !maxIdx.x)
+            // Should be just ippStsNoOperation check, but there is a bug in the function so we need additional checks
+            if(status == ippStsNoOperation && !mask.empty() && !pMaxIdx->x && !pMaxIdx->y)
             {
                 _maxIdx[0] = -1;
                 _maxIdx[1] = -1;

modules/core/test/test_arithm.cpp

@@ -1932,3 +1932,77 @@ TEST(Compare, regression_8999)
                         compare(A, B, C, CMP_LT);
                      });
 }
+
+
+TEST(Core_minMaxIdx, regression_9207_1)
+{
+    const int rows = 4;
+    const int cols = 3;
+    uchar mask_[rows*cols] = {
+ 255, 255, 255,
+ 255,   0, 255,
+   0, 255, 255,
+   0,   0, 255
+};
+    uchar src_[rows*cols] = {
+   1,   1,   1,
+   1,   1,   1,
+   2,   1,   1,
+   2,   2,   1
+};
+    Mat mask(Size(cols, rows), CV_8UC1, mask_);
+    Mat src(Size(cols, rows), CV_8UC1, src_);
+    double minVal = -0.0, maxVal = -0.0;
+    int minIdx[2] = { -2, -2 }, maxIdx[2] = { -2, -2 };
+    minMaxIdx(src, &minVal, &maxVal, minIdx, maxIdx, mask);
+    EXPECT_EQ(0, minIdx[0]);
+    EXPECT_EQ(0, minIdx[1]);
+    EXPECT_EQ(0, maxIdx[0]);
+    EXPECT_EQ(0, maxIdx[1]);
+}
+
+
+TEST(Core_minMaxIdx, regression_9207_2)
+{
+    const int rows = 13;
+    const int cols = 15;
+    uchar mask_[rows*cols] = {
+   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0, 255,
+   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0, 255,
+   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0, 255,
+   0, 255, 255, 255, 255,   0,   0,   0,   0,   0,   0,   0,   0,   0, 255,
+ 255,   0,   0,   0,   0, 255,   0,   0,   0,   0,   0,   0,   0,   0, 255,
+ 255,   0,   0,   0,   0,   0, 255,   0,   0,   0,   0,   0,   0, 255, 255,
+ 255,   0,   0,   0,   0,   0,   0, 255, 255,   0,   0, 255, 255, 255,   0,
+ 255,   0,   0,   0,   0,   0,   0,   0,   0, 255, 255, 255,   0, 255,   0,
+ 255,   0,   0,   0,   0,   0,   0, 255, 255,   0,   0,   0, 255, 255,   0,
+ 255,   0,   0,   0,   0,   0, 255,   0,   0,   0,   0,   0,   0, 255,   0,
+ 255,   0,   0,   0,   0, 255,   0,   0,   0,   0,   0,   0,   0,   0,   0,
+   0, 255,   0,   0,   0, 255,   0,   0,   0,   0,   0,   0,   0,   0,   0,
+   0, 255, 255, 255, 255,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0
+};
+    uchar src_[15*13] = {
+   5,   5,   5,   5,   5,   6,   5,   2,   0,   4,   6,   6,   4,   1,   0,
+   6,   5,   4,   4,   5,   6,   6,   5,   2,   0,   4,   6,   5,   2,   0,
+   3,   2,   1,   1,   2,   4,   6,   6,   4,   2,   3,   4,   4,   2,   0,
+   1,   0,   0,   0,   0,   1,   4,   5,   4,   4,   4,   4,   3,   2,   0,
+   0,   0,   0,   0,   0,   0,   2,   3,   4,   4,   4,   3,   2,   1,   0,
+   0,   0,   0,   0,   0,   0,   0,   2,   3,   4,   3,   2,   1,   0,   0,
+   0,   0,   0,   0,   0,   0,   0,   0,   0,   1,   1,   0,   0,   0,   1,
+   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   1,
+   0,   0,   0,   0,   0,   0,   0,   0,   0,   1,   1,   1,   0,   0,   1,
+   0,   0,   0,   0,   0,   0,   0,   1,   2,   4,   3,   3,   1,   0,   1,
+   0,   0,   0,   0,   0,   0,   1,   4,   5,   6,   5,   4,   3,   2,   0,
+   1,   0,   0,   0,   0,   0,   3,   5,   5,   4,   3,   4,   4,   3,   0,
+   2,   0,   0,   0,   0,   2,   5,   6,   5,   2,   2,   5,   4,   3,   0
+};
+    Mat mask(Size(cols, rows), CV_8UC1, mask_);
+    Mat src(Size(cols, rows), CV_8UC1, src_);
+    double minVal = -0.0, maxVal = -0.0;
+    int minIdx[2] = { -2, -2 }, maxIdx[2] = { -2, -2 };
+    minMaxIdx(src, &minVal, &maxVal, minIdx, maxIdx, mask);
+    EXPECT_EQ(0, minIdx[0]);
+    EXPECT_EQ(14, minIdx[1]);
+    EXPECT_EQ(0, maxIdx[0]);
+    EXPECT_EQ(14, maxIdx[1]);
+}