CV_INSTRUMENT_REGION()
double scale = 1, shift = 0;
+ int type = _src.type(), depth = CV_MAT_DEPTH(type);
+
+ if( rtype < 0 )
+ rtype = _dst.fixedType() ? _dst.depth() : depth;
+
if( norm_type == CV_MINMAX )
{
double smin = 0, smax = 0;
double dmin = MIN( a, b ), dmax = MAX( a, b );
minMaxIdx( _src, &smin, &smax, 0, 0, _mask );
scale = (dmax - dmin)*(smax - smin > DBL_EPSILON ? 1./(smax - smin) : 0);
- shift = dmin - smin*scale;
+ if( rtype == CV_32F )
+ {
+ scale = (float)scale;
+ shift = (float)dmin - (float)(smin*scale);
+ }
+ else
+ shift = dmin - smin*scale;
}
else if( norm_type == CV_L2 || norm_type == CV_L1 || norm_type == CV_C )
{
else
CV_Error( CV_StsBadArg, "Unknown/unsupported norm type" );
- int type = _src.type(), depth = CV_MAT_DEPTH(type);
- if( rtype < 0 )
- rtype = _dst.fixedType() ? _dst.depth() : depth;
-
CV_OCL_RUN(_dst.isUMat(),
ocl_normalize(_src, _dst, _mask, rtype, scale, shift))
EXPECT_EQ(0, cvtest::norm(m, result, NORM_INF));
}
+TEST(Normalize, regression_6125)
+{
+ float initial_values[] = {
+ 1888, 1692, 369, 263, 199,
+ 280, 326, 129, 143, 126,
+ 233, 221, 130, 126, 150,
+ 249, 575, 574, 63, 12
+ };
+
+ Mat src(Size(20, 1), CV_32F, initial_values);
+ float min = 0., max = 400.;
+ normalize(src, src, 0, 400, NORM_MINMAX, CV_32F);
+ for(int i = 0; i < 20; i++)
+ {
+ EXPECT_GE(src.at<float>(i), min) << "Value should be >= 0";
+ EXPECT_LE(src.at<float>(i), max) << "Value should be <= 400";
+ }
+}
+
TEST(MinMaxLoc, regression_4955_nans)
{
cv::Mat one_mat(2, 2, CV_32F, cv::Scalar(1));