fixed build problems on Windows

modules/core/include/opencv2/core/core.hpp

@@ -4117,7 +4117,8 @@ public:
     int index;
 };
 
-    
+
+#if 0
 class CV_EXPORTS AlgorithmImpl;
 
 /*!
@@ -4163,7 +4164,8 @@ protected:
     
     Ptr<AlgorithmImpl> impl;
 };
-    
+#endif
+
 }
 
 #endif // __cplusplus

modules/core/include/opencv2/core/operations.hpp

@@ -3558,7 +3558,7 @@ template<typename _Tp> static inline std::ostream& operator << (std::ostream& ou
     return out;
 }
     
-template<typename _Tp> struct AlgorithmParamType {};
+/*template<typename _Tp> struct AlgorithmParamType {};
 template<> struct AlgorithmParamType<int> { enum { type = CV_PARAM_TYPE_INT }; };
 template<> struct AlgorithmParamType<double> { enum { type = CV_PARAM_TYPE_REAL }; };
 template<> struct AlgorithmParamType<string> { enum { type = CV_PARAM_TYPE_STRING }; };
@@ -3600,7 +3600,7 @@ template<typename _Tp> void Algorithm::addParam(int propId, _Tp& value, bool rea
 template<typename _Tp> void Algorithm::setParamRange(int propId, const _Tp& minVal, const _Tp& maxVal)
 {
     setParamRange_(propId, AlgorithmParamType<_Tp>::type, &minVal, &maxVal);
-}
+}*/
     
 }
 

modules/core/src/arithm.cpp

@@ -2271,7 +2271,7 @@ void cv::inRange(const InputArray& _src, const InputArray& _lowerb,
             BinaryFunc sccvtfunc = getConvertFunc(scdepth, CV_32S);
             sccvtfunc(lb.data, 0, 0, 0, (uchar*)ilbuf, 0, Size(cn, 1), 0);
             sccvtfunc(ub.data, 0, 0, 0, (uchar*)iubuf, 0, Size(cn, 1), 0);
-            int minval = getMinVal(depth), maxval = getMaxVal(depth);
+            int minval = cvRound(getMinVal(depth)), maxval = cvRound(getMaxVal(depth));
             
             for( int k = 0; k < cn; k++ )
             {

modules/core/src/mathfuncs.cpp

@@ -115,7 +115,7 @@ static void FastAtan2_32f(const float *Y, const float *X, float *angle, int len,
             a = (y >= 0 ? CV_PI*0.5 : CV_PI*1.5) -
                 x*y*(y2 + 0.43157974*x2)/(y2*y2 + x2*(0.76443945*y2 + 0.05831938*x2) + (float)DBL_EPSILON);
         }
-        angle[i] = a*scale;
+        angle[i] = (float)(a*scale);
 	}
 }
 

modules/core/src/matmul.cpp

@@ -1665,7 +1665,7 @@ diagtransform_( const T* src, T* dst, const WT* m, int len, int cn, int )
         {
             const WT* _m = m;
             for( int j = 0; j < cn; j++, _m += cn + 1 )
-                dst[j] = src[j]*_m[j] + _m[cn];
+                dst[j] = saturate_cast<T>(src[j]*_m[j] + _m[cn]);
         }
     }
 }
@@ -2600,7 +2600,7 @@ static double dotProd_8u(const uchar* src1, const uchar* src2, int len)
         __m128i z = _mm_setzero_si128();
         while( i < len0 )
         {
-            blockSize = std::min(len0 - j, blockSize0);
+            blockSize = std::min(len0 - i, blockSize0);
             __m128i s = _mm_setzero_si128();
             for( j = 0; j <= blockSize - 16; j += 16 )
             {

modules/imgproc/src/sumpixels.cpp

@@ -46,16 +46,16 @@ namespace cv
 {
 
 template<typename T, typename ST, typename QT>
-void integral_( const T* src, size_t srcstep, ST* sum, size_t sumstep,
-                QT* sqsum, size_t sqsumstep, ST* tilted, size_t tiltedstep,
+void integral_( const T* src, size_t _srcstep, ST* sum, size_t _sumstep,
+                QT* sqsum, size_t _sqsumstep, ST* tilted, size_t _tiltedstep,
                 Size size, int cn )
 {
     int x, y, k;
 
-    srcstep /= sizeof(T);
-    sumstep /= sizeof(ST);
-    tiltedstep /= sizeof(ST);
-    sqsumstep /= sizeof(QT);
+    int srcstep = (int)(_srcstep/sizeof(T));
+    int sumstep = (int)(_sumstep/sizeof(ST));
+    int tiltedstep = (int)(_tiltedstep/sizeof(ST));
+    int sqsumstep = (int)(_sqsumstep/sizeof(QT));
 
     size.width *= cn;
 

modules/imgproc/test/test_histograms.cpp

@@ -1509,7 +1509,7 @@ cvTsCalcBackProject( IplImage** images, IplImage* dst, CvHistogram* hist, int* c
 }
 
 
-int CV_CalcBackProjectTest::validate_test_results( int test_case_idx )
+int CV_CalcBackProjectTest::validate_test_results( int /*test_case_idx*/ )
 {
     int code = cvtest::TS::OK;
 

modules/imgproc/test/test_imgwarp.cpp

@@ -629,12 +629,12 @@ int CV_WarpPerspectiveTest::prepare_test_case( int test_case_idx )
 
     s[0] = Point2f(0,0);
     d[0] = Point2f(0,0);
-    s[1] = Point2f(src.cols-1,0);
-    d[1] = Point2f(dst.cols-1,0);
-    s[2] = Point2f(src.cols-1,src.rows-1);
-    d[2] = Point2f(dst.cols-1,dst.rows-1);
-    s[3] = Point2f(0,src.rows-1);
-    d[3] = Point2f(0,dst.rows-1);
+    s[1] = Point2f(src.cols-1.f,0);
+    d[1] = Point2f(dst.cols-1.f,0);
+    s[2] = Point2f(src.cols-1.f,src.rows-1.f);
+    d[2] = Point2f(dst.cols-1.f,dst.rows-1.f);
+    s[3] = Point2f(0,src.rows-1.f);
+    d[3] = Point2f(0,dst.rows-1.f);
 
     float buf[16];
     Mat tmp( 1, 16, CV_32FC1, buf );

modules/video/include/opencv2/video/background_segm.hpp

@@ -400,7 +400,7 @@ public:
 };	
 
 
-class BackgroundSubtractorMOG2 : public BackgroundSubtractor
+class CV_EXPORTS BackgroundSubtractorMOG2 : public BackgroundSubtractor
 {
 public:
     //! the default constructor

samples/cpp/brief_match_test.cpp

@@ -118,7 +118,7 @@ int main(int ac, char ** av)
   vector<Point2f> mpts_1, mpts_2;
   matches2points(matches_popcount, kpts_1, kpts_2, mpts_1, mpts_2); //Extract a list of the (x,y) location of the matches
   vector<uchar> outlier_mask;
-  Mat H = findHomography(Mat(mpts_2), Mat(mpts_1), outlier_mask, RANSAC, 1);
+  Mat H = findHomography(mpts_2, mpts_1, RANSAC, 1, outlier_mask);
 
   Mat outimg;
   drawMatches(im2, kpts_2, im1, kpts_1, matches_popcount, outimg, Scalar::all(-1), Scalar::all(-1),

samples/cpp/kmeans.cpp

@@ -54,7 +54,7 @@ int main( int /*argc*/, char** /*argv*/ )
 
         kmeans(points, clusterCount, labels, 
                TermCriteria( CV_TERMCRIT_EPS+CV_TERMCRIT_ITER, 10, 1.0),
-               3, KMEANS_PP_CENTERS, &centers);
+               3, KMEANS_PP_CENTERS, centers);
 
         img = Scalar::all(0);
 

samples/cpp/stereo_calib.cpp

@@ -230,7 +230,7 @@ StereoCalib(const vector<string>& imagelist, Size boardSize, bool useCalibrated=
     stereoRectify(cameraMatrix[0], distCoeffs[0],
                   cameraMatrix[1], distCoeffs[1],
                   imageSize, R, T, R1, R2, P1, P2, Q,
-                  1, imageSize, &validRoi[0], &validRoi[1]);
+                  CALIB_ZERO_DISPARITY, 1, imageSize, &validRoi[0], &validRoi[1]);
         
     fs.open("extrinsics.yml", CV_STORAGE_WRITE);
     if( fs.isOpened() )

samples/cpp/stereo_match.cpp

@@ -178,7 +178,7 @@ int main(int argc, char** argv)
         fs["R"] >> R;
         fs["T"] >> T;
         
-        stereoRectify( M1, D1, M2, D2, img_size, R, T, R1, R2, P1, P2, Q, -1, img_size, &roi1, &roi2 );
+        stereoRectify( M1, D1, M2, D2, img_size, R, T, R1, R2, P1, P2, Q, CALIB_ZERO_DISPARITY, -1, img_size, &roi1, &roi2 );
         
         Mat map11, map12, map21, map22;
         initUndistortRectifyMap(M1, D1, R1, P1, img_size, CV_16SC2, map11, map12);

samples/cpp/video_homography.cpp

@@ -182,7 +182,7 @@ int main(int ac, char ** av)
 
             if (matches.size() > 5)
             {
-                Mat H = findHomography(Mat(train_pts), Mat(query_pts), match_mask, RANSAC, 4);
+                Mat H = findHomography(train_pts, query_pts, RANSAC, 4, match_mask);
                 if (countNonZero(Mat(match_mask)) > 15)
                 {
                     H_prev = H;

samples/gpu/morfology.cpp

@@ -41,7 +41,7 @@ void OpenClose(int, void*)
 		cv::gpu::morphologyEx(src, dst, CV_MOP_OPEN, element);
     else
         cv::gpu::morphologyEx(src, dst, CV_MOP_CLOSE, element);
-    imshow("Open/Close",dst);
+    imshow("Open/Close",(Mat)dst);
 }
 
 // callback function for erode/dilate trackbar
@@ -54,7 +54,7 @@ void ErodeDilate(int, void*)
         cv::gpu::erode(src, dst, element);
     else
         cv::gpu::dilate(src, dst, element);
-    imshow("Erode/Dilate",dst);
+    imshow("Erode/Dilate",(Mat)dst);
 }
 
 

samples/gpu/performance/tests.cpp

@@ -784,10 +784,10 @@ TEST(projectPoints)
 
 
 void InitSolvePnpRansac()
-{
-    Mat object; gen(object, 1, 4, CV_32FC3, Scalar::all(0), Scalar::all(100));
-    Mat image; gen(image, 1, 4, CV_32FC2, Scalar::all(0), Scalar::all(100));
-    Mat rvec, tvec;
+{
+    Mat object; gen(object, 1, 4, CV_32FC3, Scalar::all(0), Scalar::all(100));
+    Mat image; gen(image, 1, 4, CV_32FC2, Scalar::all(0), Scalar::all(100));
+    Mat rvec, tvec;
     gpu::solvePnPRansac(object, image, Mat::eye(3, 3, CV_32F), Mat(), rvec, tvec);
 }
 
@@ -796,31 +796,31 @@ TEST(solvePnPRansac)
 {
     InitSolvePnpRansac();
 
-    for (int num_points = 5000; num_points <= 300000; num_points = int(num_points * 3.76))
-    {
-        SUBTEST << "num_points " << num_points;
-
-        Mat object; gen(object, 1, num_points, CV_32FC3, Scalar::all(10), Scalar::all(100));
-        Mat image; gen(image, 1, num_points, CV_32FC2, Scalar::all(10), Scalar::all(100));
-        Mat camera_mat; gen(camera_mat, 3, 3, CV_32F, 0.5, 1);
-        camera_mat.at<float>(0, 1) = 0.f;
-        camera_mat.at<float>(1, 0) = 0.f;
-        camera_mat.at<float>(2, 0) = 0.f;
-        camera_mat.at<float>(2, 1) = 0.f;
-
-        Mat rvec, tvec;
-        const int num_iters = 200;
-        const float max_dist = 2.0f;
-        vector<int> inliers_cpu, inliers_gpu;
-
-        CPU_ON;
-        solvePnPRansac(object, image, camera_mat, Mat(), rvec, tvec, false, num_iters, 
-                       max_dist, int(num_points * 0.05), &inliers_cpu);
-        CPU_OFF;
-
-        GPU_ON;
-        gpu::solvePnPRansac(object, image, camera_mat, Mat(), rvec, tvec, false, num_iters,
-                            max_dist, int(num_points * 0.05), &inliers_gpu);
+    for (int num_points = 5000; num_points <= 300000; num_points = int(num_points * 3.76))
+    {
+        SUBTEST << "num_points " << num_points;
+
+        Mat object; gen(object, 1, num_points, CV_32FC3, Scalar::all(10), Scalar::all(100));
+        Mat image; gen(image, 1, num_points, CV_32FC2, Scalar::all(10), Scalar::all(100));
+        Mat camera_mat; gen(camera_mat, 3, 3, CV_32F, 0.5, 1);
+        camera_mat.at<float>(0, 1) = 0.f;
+        camera_mat.at<float>(1, 0) = 0.f;
+        camera_mat.at<float>(2, 0) = 0.f;
+        camera_mat.at<float>(2, 1) = 0.f;
+
+        Mat rvec, tvec;
+        const int num_iters = 200;
+        const float max_dist = 2.0f;
+        vector<int> inliers_cpu, inliers_gpu;
+
+        CPU_ON;
+        solvePnPRansac(object, image, camera_mat, Mat(), rvec, tvec, false, num_iters, 
+                       max_dist, int(num_points * 0.05), inliers_cpu);
+        CPU_OFF;
+
+        GPU_ON;
+        gpu::solvePnPRansac(object, image, camera_mat, Mat(), rvec, tvec, false, num_iters,
+                            max_dist, int(num_points * 0.05), &inliers_gpu);
         GPU_OFF;
     }
 }