moved gtest to modules; added some gtest-based tests

3rdparty/CMakeLists.txt

@@ -16,7 +16,3 @@ endif()
 if(WITH_TIFF AND NOT TIFF_FOUND)
 	add_subdirectory(libtiff)
 endif()
-
-if(0)
-add_subdirectory(gtest)
-endif()

3rdparty/gtest/CMakeLists.txt

-project(opencv_gtest)
-
-# List of C++ files:
-
-include_directories("${CMAKE_CURRENT_SOURCE_DIR}/..")
-
-# The .cpp files:
-file(GLOB lib_srcs *.cpp)
-file(GLOB lib_hdrs *.h)
-
-# ----------------------------------------------------------------------------------
-# 				Define the library target:
-# ----------------------------------------------------------------------------------
-
-set(the_target "opencv_gtest")
-
-add_library(${the_target} STATIC ${lib_srcs} ${lib_hdrs})
-
-if(UNIX)
-     if(CMAKE_COMPILER_IS_GNUCXX OR CV_ICC)
-        set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -fPIC")
-     endif()
-endif()
-
-set_target_properties(${the_target}
-	PROPERTIES OUTPUT_NAME "${the_target}"
-	DEBUG_POSTFIX "${OPENCV_DEBUG_POSTFIX}"
-	ARCHIVE_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/3rdparty/lib
-	)

modules/CMakeLists.txt

@@ -13,6 +13,7 @@ if(MSVC OR MINGW)
    endif()
 endif()
 
+add_subdirectory(gtest)
 add_subdirectory(highgui)
 add_subdirectory(imgproc)
 add_subdirectory(legacy)

modules/core/test/precomp.cpp

+#include "precomp.hpp"

modules/core/test/precomp.hpp

+#include "opencv2/gtest/gtestcv.hpp"
+#include "opencv2/core/core.hpp"

modules/core/test/test_arithm.cpp

+#include "precomp.hpp"
+
+using namespace cv;
+
+TEST(ArithmTest, add)
+{
+    typedef uchar _Tp;
+    
+    Mat A(30,30,DataType<_Tp>::type), B(A.size(), A.type()), C0, C;
+    RNG rng(-1);
+    rng.fill(A, RNG::UNIFORM, Scalar::all(0), Scalar::all(256));
+    rng.fill(B, RNG::UNIFORM, Scalar::all(0), Scalar::all(256));
+    C0.create(A.size(), A.type());
+    int i, j, cols = A.cols*A.channels();
+    for(i = 0; i < A.rows; i++)
+    {
+        const _Tp* aptr = A.ptr<_Tp>(i);
+        const _Tp* bptr = B.ptr<_Tp>(i);
+        _Tp* cptr = C0.ptr<_Tp>(i);
+        for(j = 0; j < cols; j++)
+            cptr[j] = saturate_cast<_Tp>(aptr[j] + bptr[j]);
+    }
+    add(A, B, C);
+    EXPECT_EQ(norm(C, C0, NORM_INF), 0);
+}

modules/core/test/test_main.cpp

+#include "precomp.hpp"
+#include "opencv2/gtest/gtest_main.hpp"

modules/gtest/CMakeLists.txt

+if(BUILD_SHARED_LIBS)
+add_definitions(-DGTEST_CREATE_SHARED_LIBRARY=1)
+endif()
+define_opencv_module(gtest opencv_core)

3rdparty/gtest/README → modules/gtest/README

+The new OpenCV test engine is based
+on the Google C++ Testing Framework (GTest).
+Below is the original GTest README.
+-----------------------------------
+
 Google C++ Testing Framework
 ============================
 

modules/gtest/include/opencv2/gtest/gtest_main.hpp

+int main(int argc, char **argv)
+{
+    ::testing::InitGoogleTest(&argc, argv);
+    return RUN_ALL_TESTS();
+}

modules/gtest/include/opencv2/gtest/gtestcv.hpp

+#ifndef __OPENCV_GTESTCV_HPP__
+#define __OPENCV_GTESTCV_HPP__
+
+#include "opencv2/gtest/gtest.h"
+#include "opencv2/core/core.hpp"
+
+namespace cvtest
+{
+
+using std::vector;
+using cv::RNG;
+using cv::Mat;
+using cv::Scalar;
+using cv::Size;
+using cv::Point;
+using cv::Rect;
+
+enum
+{
+    TYPE_MASK_8U = 1 << CV_8U,
+    TYPE_MASK_8S = 1 << CV_8S,
+    TYPE_MASK_16U = 1 << CV_16U,
+    TYPE_MASK_16S = 1 << CV_16S,
+    TYPE_MASK_32S = 1 << CV_32S,
+    TYPE_MASK_32F = 1 << CV_32F,
+    TYPE_MASK_64F = 1 << CV_64F,
+    TYPE_MASK_ALL = (TYPE_MASK_64F<<1)-1,
+    TYPE_MASK_ALL_BUT_8S = TYPE_MASK_ALL & ~TYPE_MASK_8S
+};
+    
+CV_EXPORTS Size randomSize(RNG& rng, double maxSizeLog);
+CV_EXPORTS void randomSize(RNG& rng, int minDims, int maxDims, double maxSizeLog, vector<int>& sz);    
+CV_EXPORTS int randomType(RNG& rng, int typeMask, int minChannels, int maxChannels);
+CV_EXPORTS Mat randomMat(RNG& rng, Size size, int type, bool useRoi);
+CV_EXPORTS Mat randomMat(RNG& rng, const vector<int>& size, int type, bool useRoi);
+CV_EXPORTS Mat add(const Mat& a, double alpha, const Mat& b, double beta,
+                      Scalar gamma, Mat& c, int ctype, bool calcAbs);
+CV_EXPORTS void convert(const Mat& src, Mat& dst, int dtype, double alpha, double beta);
+CV_EXPORTS void copy(const Mat& src, Mat& dst, const Mat& mask=Mat());
+CV_EXPORTS void set(Mat& dst, const Scalar& gamma, const Mat& mask=Mat());
+CV_EXPORTS void minMaxFilter(const Mat& a, Mat& maxresult, const Mat& minresult, const Mat& kernel, Point anchor);
+CV_EXPORTS void filter2D(const Mat& src, Mat& dst, int ddepth, const Mat& kernel, Point anchor, double delta, int borderType);
+CV_EXPORTS void copyMakeBorder(const Mat& src, Mat& dst, int top, int bottom, int left, int right, int borderType, Scalar borderValue);
+CV_EXPORTS void minMaxLoc(const Mat& src, double* maxval, double* minval,
+                          vector<int>* maxloc, vector<int>* minloc, const Mat& mask=Mat());
+CV_EXPORTS double norm(const Mat& src, int normType, const Mat& mask=Mat());
+CV_EXPORTS double norm(const Mat& src1, const Mat& src2, int normType, const Mat& mask=Mat());
+CV_EXPORTS bool cmpEps(const Mat& src1, const Mat& src2, double maxDiff, vector<int>* loc);
+CV_EXPORTS void logicOp(const Mat& src1, const Mat& src2, Mat& dst, char c);
+CV_EXPORTS void logicOp(const Mat& src, const Scalar& s, Mat& dst, char c);
+CV_EXPORTS void compare(const Mat& src1, const Mat& src2, Mat& dst, int cmpop);
+CV_EXPORTS void compare(const Mat& src, const Scalar& s, Mat& dst, int cmpop);    
+CV_EXPORTS void gemm(const Mat& src1, const Mat& src2, double alpha,
+                     const Mat& src3, double beta, Mat& dst, int flags);
+CV_EXPORTS void crosscorr(const Mat& src1, const Mat& src2, Mat& dst, int dtype);
+
+}
+
+#endif
+

3rdparty/gtest/gtest.cpp → modules/gtest/src/gtest.cpp

@@ -36,7 +36,7 @@
 
 // This line ensures that gtest.h can be compiled on its own, even
 // when it's fused.
-#include <gtest/gtest.h>
+#include "precomp.hpp"
 
 // The following lines pull in the real gtest *.cc files.
 // Copyright 2005, Google Inc.

modules/gtest/src/gtestcv.cpp

+#include "precomp.hpp"
+
+using namespace cv;
+
+namespace cvtest
+{
+
+Size randomSize(RNG& rng, double maxSizeLog)
+{
+    double width_log = rng.uniform(0., maxSizeLog);
+    double height_log = rng.uniform(0., maxSizeLog - width_log);
+    if( (unsigned)rng % 2 != 0 )
+        std::swap(width_log, height_log);
+    Size sz;
+    sz.width = cvRound(exp(width_log));
+    sz.height = cvRound(exp(height_log));
+    return sz;
+}
+
+void randomSize(RNG& rng, int minDims, int maxDims, double maxSizeLog, vector<int>& sz)
+{
+    int i, dims = rng.uniform(minDims, maxDims+1);
+    sz.resize(dims);
+    for( i = 0; i < dims; i++ )
+    {
+        double v = rng.uniform(0., maxSizeLog);
+        maxSizeLog -= v;
+        sz[i] = cvRound(exp(v));
+    }
+    for( i = 0; i < dims; i++ )
+    {
+        int j = rng.uniform(0, dims);
+        int k = rng.uniform(0, dims);
+        std::swap(sz[j], sz[k]);
+    }
+}
+
+int randomType(RNG& rng, int typeMask, int minChannels, int maxChannels)
+{
+    int channels = rng.uniform(minChannels, maxChannels+1);
+    int depth = 0;
+    CV_Assert((typeMask & TYPE_MASK_ALL) != 0);
+    for(;;)
+    {
+        depth = rng.uniform(CV_8U, CV_64F+1);
+        if( ((1 << depth) & typeMask) != 0 )
+            break;
+    }
+    return CV_MAKETYPE(depth, channels);
+}
+
+Mat randomMat(RNG& rng, Size size, int type, bool useRoi)
+{
+    
+}
+
+Mat randomMat(RNG& rng, const vector<int>& size, int type, bool useRoi)
+{
+}
+    
+Mat add(const Mat& _a, double alpha, const Mat& _b, double beta,
+        Scalar gamma, Mat& c, int ctype, bool calcAbs)
+{
+    Mat a = _a, b = _b;
+    if( a.empty() || alpha == 0 )
+    {
+        // both alpha and beta can be 0, but at least one of a and b must be non-empty array,
+        // otherwise we do not know the size of the output (and may be type of the output, when ctype<0)
+        CV_Assert( !a.empty() || !b.empty() );
+        if( !b.empty() )
+        {
+            a = b;
+            alpha = beta;
+            b = Mat();
+            beta = 0;
+        }
+    }
+    if( b.empty() || beta == 0 )
+    {
+        b = Mat();
+        beta = 0;
+    }
+    else
+        CV_Assert(a.size == b.size);
+    
+    if( ctype < 0 )
+        ctype = a.depth();
+    ctype = CV_MAKETYPE(CV_MAT_DEPTH(ctype), a.channels());
+    c.create(a.dims, &a.size[0], ctype);
+    const Mat *arrays[3];
+    Mat planes[3], buf[3];
+    arrays[0] = &a;
+    arrays[1] = b.empty() ? 0 : &b;
+    arrays[2] = &c;
+    
+    NAryMatIterator it(arrays, planes, 3);
+    int i, nplanes = it.nplanes, cn=a.channels();
+    size_t total = planes[0].total(), maxsize = min(12*12*max(12/cn, 1), total);
+    
+    CV_Assert(planes[0].rows == 1);
+    buf[0].create(1, (int)maxsize, CV_64FC(cn));
+    if(!b.empty())
+        buf[1].create(1, maxsize, CV_64FC(cn));
+    buf[2].create(1, maxsize, CV_64FC(cn));
+    scalarToRawData(gamma, buf[2].data, CV_64FC(cn), (int)(maxsize*cn));
+    
+    for( i = 0; i < nplanes; i++, ++it)
+    {
+        for( size_t j = 0; j < total; j += maxsize )
+        {
+            size_t j2 = min(j + maxsize, total);
+            Mat apart0 = planes[0].colRange((int)j, (int)j2);
+            Mat cpart0 = planes[2].colRange((int)j, (int)j2);
+            Mat apart = buf[0].colRange(0, (int)(j2 - j));
+            
+            apart0.convertTo(apart, apart.type(), alpha);
+            size_t k, n = (j2 - j)*cn;
+            double* aptr = (double*)apart.data;
+            const double* gptr = (const double*)buf[2].data;
+            
+            if( b.empty() )
+            {
+                for( k = 0; k < n; k++ )
+                    aptr[k] += gptr[k];
+            }
+            else
+            {
+                Mat bpart0 = planes[1].colRange((int)j, (int)j2);
+                Mat bpart = buf[1].colRange(0, (int)(j2 - j));
+                bpart0.convertTo(bpart, bpart.type(), beta);
+                const double* bptr = (const double*)bpart.data;
+                
+                for( k = 0; k < n; k++ )
+                    aptr[k] += bptr[k] + gptr[k];
+            }
+            if( calcAbs )
+                for( k = 0; k < n; k++ )
+                    aptr[k] = fabs(aptr[k]);
+            apart.convertTo(cpart0, cpart0.type(), 1, 0);
+        }
+    }
+}
+
+
+static template<typename _Tp1, typename _Tp2> inline void
+convert(const _Tp1* src, _Tp2* dst, size_t total, double alpha, double beta)
+{
+    size_t i;
+    if( alpha == 1 && beta == 0 )
+        for( i = 0; i < total; i++ )
+            dst[i] = saturate_cast<_Tp2>(src[i]);
+    else if( beta == 0 )
+        for( i = 0; i < total; i++ )
+            dst[i] = saturate_cast<_Tp2>(src[i]*alpha);
+    else
+        for( i = 0; i < total; i++ )
+            dst[i] = saturate_cast<_Tp2>(src[i]*alpha + beta);
+}
+    
+void convert(const Mat& src, Mat& dst, int dtype, double alpha, double beta)
+{
+    dtype = CV_MAKETYPE(CV_MAT_DEPTH(dtype), src.channels());
+    dst.create(src.dims, &src.size[0], dtype);
+    if( alpha == 0 )
+    {
+        set( dst, Scalar::all(beta) );
+        return;
+    }
+    if( dtype == src.type() && alpha == 1 && beta == 0 )
+    {
+        copy( src, dst );
+        return;
+    }
+    
+    const Mat *arrays[]={&src, &dst};
+    Mat planes[2];
+    
+    NAryMatIterator it(arrays, planes, 2);
+    size_t j, total = total = planes[0].total()*planes[0].channels();
+    int i, nplanes = it.nplanes;
+    
+    for( i = 0; i < nplanes; i++, ++it)
+    {
+        const uchar* sptr = planes[0].data;
+        uchar* dptr = planes[1].data;
+        
+        switch( src.depth() )
+        {
+        case 
+        
+        }
+        
+        for( j = 0; j < total; j++, sptr += elemSize, dptr += elemSize )
+        {
+            if( mptr[j] )
+                for( k = 0; k < elemSize; k++ )
+                    dptr[k] = sptr[k];
+        }
+    }
+}
+    
+     
+void copy(const Mat& src, Mat& dst, const Mat& mask)
+{
+    dst.create(src.dims, &src.size[0], src.type());
+    
+    if(mask.empty())
+    {
+        const Mat* arrays[] = {&src, &dst};
+        Mat planes[2];
+        NAryMatIterator it(arrays, planes, 2);
+        int i, nplanes = it.nplanes;
+        size_t planeSize = planes[0].total()*src.elemSize();
+        
+        for( i = 0; i < nplanes; i++, ++it )
+            memcpy(planes[1].data, planes[0].data, planeSize);
+        
+        return;
+    }
+    
+    CV_Assert( src.size == mask.size && mask.type() == CV_8U );
+    
+    const Mat *arrays[3]={&src, &dst, &mask};
+    Mat planes[3];
+    
+    NAryMatIterator it(arrays, planes, 3);
+    size_t j, k, elemSize = src.elemSize(), total = planes[0].total();
+    int i, nplanes = it.nplanes;
+    
+    for( i = 0; i < nplanes; i++, ++it)
+    {
+        const uchar* sptr = planes[0].data;
+        uchar* dptr = planes[1].data;
+        const uchar* mptr = planes[2].data;
+        
+        for( j = 0; j < total; j++, sptr += elemSize, dptr += elemSize )
+        {
+            if( mptr[j] )
+                for( k = 0; k < elemSize; k++ )
+                    dptr[k] = sptr[k];
+        }
+    }
+}
+
+    
+void set(Mat& dst, const Scalar& gamma, const Mat& mask)
+{
+    double buf[12];
+    scalarToRawData(gama, &buf, dst.type(), dst.channels());
+    const uchar* gptr = (const uchar*)&buf[0];
+    
+    if(mask.empty())
+    {
+        const Mat* arrays[] = {&dst};
+        Mat plane;
+        NAryMatIterator it(arrays, &plane, 1);
+        int i, nplanes = it.nplanes;
+        size_t j, k, elemSize = dst.elemSize(), planeSize = planes[0].total()*elemSize;
+        
+        for( k = 1; k < elemSize; k++ )
+            if( gptr[k] != gptr[0] )
+                break;
+        bool uniform = k >= elemSize;
+        
+        for( i = 0; i < nplanes; i++, ++it )
+        {
+            uchar* dptr = plane.data;
+            if( uniform )
+                memset( dptr, gptr[0], planeSize );
+            else if( i == 0 )
+            {
+                for( j = 0; j < planeSize; j += elemSize, dptr += elemSize )
+                    for( k = 0; k < elemSize; k++ )
+                        dptr[k] = gptr[k];
+            }
+            else
+                memcpy(dtr, dst.data, planeSize);
+        }
+        return;
+    }
+    
+    CV_Assert( dst.size == mask.size && mask.type() == CV_8U );
+    
+    const Mat *arrays[2]={&dst, &mask};
+    Mat planes[2];
+    
+    NAryMatIterator it(arrays, planes, 2);
+    size_t j, k, elemSize = src.elemSize(), total = planes[0].total();
+    int i, nplanes = it.nplanes;
+    
+    for( i = 0; i < nplanes; i++, ++it)
+    {
+        uchar* dptr = planes[0].data;
+        const uchar* mptr = planes[1].data;
+        
+        for( j = 0; j < total; j++, dptr += elemSize )
+        {
+            if( mptr[j] )
+                for( k = 0; k < elemSize; k++ )
+                    dptr[k] = gptr[k];
+        }
+    }
+}
+    
+    
+void minMaxFilter(const Mat& a, Mat& maxresult, const Mat& minresult, const Mat& kernel, Point anchor);
+void filter2D(const Mat& src, Mat& dst, int ddepth, const Mat& kernel, Point anchor, double delta, int borderType);
+void copyMakeBorder(const Mat& src, Mat& dst, int top, int bottom, int left, int right, int borderType, Scalar borderValue);
+void minMaxLoc(const Mat& src, double* maxval, double* minval,
+               vector<int>* maxloc, vector<int>* minloc, const Mat& mask=Mat());
+double norm(const Mat& src, int normType, const Mat& mask=Mat());
+double norm(const Mat& src1, const Mat& src2, int normType, const Mat& mask=Mat());
+bool cmpEps(const Mat& src1, const Mat& src2, int int_maxdiff, int flt_maxulp, vector<int>* loc);
+void logicOp(const Mat& src1, const Mat& src2, Mat& dst, char c);
+void logicOp(const Mat& src, const Scalar& s, Mat& dst, char c);
+void compare(const Mat& src1, const Mat& src2, Mat& dst, int cmpop);
+void compare(const Mat& src, const Scalar& s, Mat& dst, int cmpop);    
+
+}

modules/gtest/src/precomp.cpp

+#include "precomp.hpp"

modules/gtest/src/precomp.hpp

+#include "opencv2/gtest/gtestcv.hpp"