* Simulated Annealing for ANN_MLP training method
* EXPECT_LT
* just to test new data
* manage RNG
* Try again
* Just run buildbot with new data
* try to understand
* Test layer
* New data- new test
* Force RNG in backprop
* Use Impl to avoid virtual method
* reset all weights
* try to solve ABI
* retry
* ABI solved?
* till problem with dynamic_cast
* Something is wrong
* Solved?
* disable backprop test
* remove ANN_MLP_ANNEALImpl
* Disable weight in varmap
* Add example for SimulatedAnnealing
* Fix issue #10114
Convert table change
From:
CV_8U -> HALF
CV_8S -> HALF
CV_16U -> UINT
CV_16S -> UINT
CV_32S -> UINT
CV_32F -> FLOAT
To:
CV_8U -> HALF
CV_8S -> HALF
CV_16U -> UINT
CV_16S -> FLOAT
CV_32S -> FLOAT loss precision
CV_32F -> FLOAT
Signed integer can't be presented well with UINT. Even adjust bias, CV16S and CV32S will be confused when load from exr file.
Also fix CV_8S negative value incorrect bug
* EXR import and export
imread() from EXR returns CV_32F only
imwrite() accepts CV_32 cv::Mat only and stores FLOAT images by default. Add imwrite() flag to store in HALF format.
* fix compiling error
* clean up
* fix EXR import issues
* remove raw SSE2/NEON implementation from convert.cpp
* remove raw implementation from Cvt_SIMD
* remove raw implementation from cvtScale_SIMD
* remove raw implementation from cvtScaleAbs_SIMD
* remove duplicated implementation cvt_<float, short>
* remove duplicated implementation cvtScale_<short, short, float>
* add "from double" version of Cvt_SIMD
* modify the condition of test ConvertScaleAbs
* Update convert.cpp
fixed crash in cvtScaleAbs(8s=>8u)
* fixed compile error on Win32
* fixed several test failures because of accuracy loss in cvtScale(int=>int)
* fixed NEON implementation of v_cvt_f64(int=>double) intrinsic
* another attempt to fix test failures
* keep trying to fix the test failures and just introduced compile warnings
* fixed one remaining test (subtractScalar)