Fix x64 build warnings

modules/core/test/test_mat.cpp

@@ -869,7 +869,7 @@ int calcDiffElemCountImpl(const vector<Mat>& mv, const Mat& m)
         for(int x = 0; x < m.cols; x++)
         {
             const ElemType* mElem = &m.at<ElemType>(y,x*mChannels);
-            int loc = 0;
+            size_t loc = 0;
             for(size_t i = 0; i < mv.size(); i++)
             {
                 const size_t mvChannel = mv[i].channels();
@@ -879,7 +879,7 @@ int calcDiffElemCountImpl(const vector<Mat>& mv, const Mat& m)
                         diffElemCount++;
                 loc += mvChannel;
             }
-            CV_Assert(loc == mChannels);
+            CV_Assert(loc == (size_t)mChannels);
         }
     }
     return diffElemCount;

modules/imgproc/src/demosaicing.cpp

@@ -1306,7 +1306,7 @@ public:
         int dcn = dst.channels();
         int dcn2 = dcn<<1;
         int start_with_green = Start_with_green, blue = Blue;
-        int sstep = src.step / src.elemSize1(), dstep = dst.step / dst.elemSize1();
+        int sstep = int(src.step / src.elemSize1()), dstep = int(dst.step / dst.elemSize1());
         SIMDInterpolator vecOp;
 
         const T* S = reinterpret_cast<const T*>(src.data + (range.start + 1) * src.step) + 1;
@@ -1415,7 +1415,7 @@ static void Bayer2RGB_EdgeAware_T(const Mat& src, Mat& dst, int code)
     }
     size = dst.size();
     size.width *= dst.channels();
-    int dstep = dst.step / dst.elemSize1();
+    size_t dstep = dst.step / dst.elemSize1();
     T* firstRow = reinterpret_cast<T*>(dst.data);
     T* lastRow = reinterpret_cast<T*>(dst.data) + (size.height-1) * dstep;
 
@@ -1423,8 +1423,8 @@ static void Bayer2RGB_EdgeAware_T(const Mat& src, Mat& dst, int code)
     {
         for (int x = 0; x < size.width; ++x)
         {
-            firstRow[x] = firstRow[dstep+x];
+            firstRow[x] = (firstRow+dstep)[x];
-            lastRow[x] = lastRow[-dstep+x];
+            lastRow[x] = (lastRow-dstep)[x];
         }
     }
     else

modules/imgproc/src/floodfill.cpp

@@ -505,14 +505,15 @@ int cv::floodFill( InputOutputArray _image, InputOutputArray _mask,
 
     if( is_simple )
     {
-        int elem_size = img.elemSize();
+        size_t elem_size = img.elemSize();
         const uchar* seed_ptr = img.data + img.step*seedPoint.y + elem_size*seedPoint.x;
 
-        for(i = 0; i < elem_size; i++)
+        size_t k = 0;
-            if (seed_ptr[i] != nv_buf.b[i])
+        for(; k < elem_size; k++)
+            if (seed_ptr[k] != nv_buf.b[k])
                 break;
 
-        if( i != elem_size )
+        if( k != elem_size )
         {
             if( type == CV_8UC1 )
                 floodFill_CnIR(img, seedPoint, nv_buf.b[0], &comp, flags, &buffer);

modules/imgproc/src/samplers.cpp

@@ -46,7 +46,7 @@ namespace cv
 {
 
 static const uchar*
-adjustRect( const uchar* src, int src_step, int pix_size,
+adjustRect( const uchar* src, size_t src_step, int pix_size,
            Size src_size, Size win_size,
            Point ip, Rect* pRect )
 {
@@ -127,8 +127,8 @@ struct nop
 
 
 template<typename _Tp, typename _DTp, typename _WTp, class ScaleOp, class CastOp>
-void getRectSubPix_Cn_(const _Tp* src, int src_step, Size src_size,
+void getRectSubPix_Cn_(const _Tp* src, size_t src_step, Size src_size,
-                       _DTp* dst, int dst_step, Size win_size, Point2f center, int cn )
+                       _DTp* dst, size_t dst_step, Size win_size, Point2f center, int cn )
 {
     ScaleOp scale_op;
     CastOp cast_op;
@@ -217,8 +217,8 @@ void getRectSubPix_Cn_(const _Tp* src, int src_step, Size src_size,
 
 
 static void getRectSubPix_8u32f
-( const uchar* src, int src_step, Size src_size,
+( const uchar* src, size_t src_step, Size src_size,
- float* dst, int dst_step, Size win_size, Point2f center0, int cn )
+ float* dst, size_t dst_step, Size win_size, Point2f center0, int cn )
 {
     Point2f center = center0;
     Point ip;
@@ -269,8 +269,8 @@ static void getRectSubPix_8u32f
 
 
 static void
-getQuadrangleSubPix_8u32f_CnR( const uchar* src, int src_step, Size src_size,
+getQuadrangleSubPix_8u32f_CnR( const uchar* src, size_t src_step, Size src_size,
-                               float* dst, int dst_step, Size win_size,
+                               float* dst, size_t dst_step, Size win_size,
                                const double *matrix, int cn )
 {
     int x, y, k;

modules/imgproc/src/segmentation.cpp

@@ -148,9 +148,9 @@ void cv::watershed( InputArray _src, InputOutputArray _markers )
     CV_Assert( src.size() == dst.size() );
 
     const uchar* img = src.data;
-    int istep = src.step/sizeof(img[0]);
+    int istep = int(src.step/sizeof(img[0]));
     int* mask = dst.ptr<int>();
-    int mstep = dst.step / sizeof(mask[0]);
+    int mstep = int(dst.step / sizeof(mask[0]));
 
     for( i = 0; i < 256; i++ )
         subs_tab[i] = 0;

modules/softcascade/CMakeLists.txt

@@ -1,2 +1,3 @@
 set(the_description "Soft Cascade detection and training")
-ocv_define_module(softcascade opencv_core opencv_imgproc opencv_ml)
+ocv_define_module(softcascade opencv_core opencv_imgproc opencv_ml)
+ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4310)

modules/softcascade/src/_random.hpp

@@ -52,6 +52,7 @@ namespace cv { namespace softcascade { namespace internal
 struct Random
 {
     typedef std::mt19937 engine;
+    typedef engine::result_type seed_type;
     typedef std::uniform_int<int> uniform;
 };
 
@@ -67,6 +68,7 @@ namespace cv { namespace softcascade { namespace internal
 struct Random
 {
     typedef std::mt19937 engine;
+    typedef engine::result_type seed_type;
 // True if we're using C++11.
 #if __cplusplus >= 201103L
     // C++11 removes uniform_int.
@@ -86,6 +88,7 @@ namespace cv { namespace softcascade { namespace internal
 struct Random
 {
     typedef std::tr1::mt19937 engine;
+    typedef engine::result_type seed_type;
     typedef std::tr1::uniform_int<int> uniform;
 };
 
@@ -125,6 +128,7 @@ private:
 struct Random
 {
     typedef rnd::engine engine;
+    typedef uint64 seed_type;
     typedef rnd::uniform_int<int> uniform;
 };
 

modules/softcascade/src/integral_channel_builder.cpp

@@ -217,7 +217,7 @@ void ChannelFeaturePool::fill(int desired)
     int nfeatures = std::min(desired, maxPoolSize);
     pool.reserve(nfeatures);
 
-    Random::engine eng(FEATURE_RECT_SEED);
+    Random::engine eng((Random::seed_type)FEATURE_RECT_SEED);
     Random::engine eng_ch(DCHANNELS_SEED);
 
     Random::uniform chRand(0, N_CHANNELS - 1);

modules/softcascade/src/soft_cascade_octave.cpp

@@ -116,7 +116,7 @@ BoostedSoftCascadeOctave::BoostedSoftCascadeOctave(cv::Rect bb, int np, int nn,
         _params.truncate_pruned_tree = false;
         _params.use_surrogates       = false;
         _params.use_1se_rule         = false;
-        _params.regression_accuracy  = 1.0e-6;
+        _params.regression_accuracy  = 1.0e-6f;
 
         // boost params
         _params.boost_type           = CvBoost::GENTLE;
@@ -221,7 +221,7 @@ void BoostedSoftCascadeOctave::generateNegatives(const Dataset* dataset)
     using namespace cv::softcascade::internal;
     // ToDo: set seed, use offsets
     Random::engine eng(DX_DY_SEED);
-    Random::engine idxEng(INDEX_ENGINE_SEED);
+    Random::engine idxEng((Random::seed_type)INDEX_ENGINE_SEED);
 
     int h = boundingBox.height;
 

modules/softcascade/src/softcascade.cpp

@@ -180,7 +180,7 @@ struct ChannelStorage
     cv::Mat hog;
     int shrinkage;
     int offset;
-    int step;
+    size_t step;
     int model_height;
 
     cv::Ptr<ChannelFeatureBuilder> builder;
@@ -398,7 +398,7 @@ struct Detector::Fields
                 fns = (*st)[SC_INTERNAL];
                 FileNodeIterator inIt = fns.begin(), inIt_end = fns.end();
                 for (; inIt != inIt_end;)
-                    nodes.push_back(Node(features.size(), inIt));
+                    nodes.push_back(Node((int)features.size(), inIt));
 
                 fns = (*st)[SC_LEAF];
                 inIt = fns.begin(), inIt_end = fns.end();
@@ -504,7 +504,7 @@ void Detector::detectNoRoi(const cv::Mat& image, std::vector<Detection>& objects
         {
             for (int dx = 0; dx < level.workRect.width; ++dx)
             {
-                storage.offset = dy * storage.step + dx;
+                storage.offset = (int)(dy * storage.step + dx);
                 fld.detectAt(dx, dy, level, storage, objects);
             }
         }
@@ -555,7 +555,7 @@ void Detector::detect(cv::InputArray _image, cv::InputArray _rois, std::vector<D
              {
                  if (m[dx])
                  {
-                     storage.offset = dy * storage.step + dx;
+                     storage.offset = (int)(dy * storage.step + dx);
                      fld.detectAt(dx, dy, level, storage, objects);
                  }
              }
@@ -570,11 +570,11 @@ void Detector::detect(InputArray _image, InputArray _rois,  OutputArray _rects,
     std::vector<Detection> objects;
     detect( _image, _rois, objects);
 
-    _rects.create(1, objects.size(), CV_32SC4);
+    _rects.create(1, (int)objects.size(), CV_32SC4);
     cv::Mat_<cv::Rect> rects = (cv::Mat_<cv::Rect>)_rects.getMat();
     cv::Rect* rectPtr = rects.ptr<cv::Rect>(0);
 
-    _confs.create(1, objects.size(), CV_32F);
+    _confs.create(1, (int)objects.size(), CV_32F);
     cv::Mat confs = _confs.getMat();
     float* confPtr = confs.ptr<float>(0);