got rid of Blob and BlobShape completely; use cv::Mat and std::vector<int> instead

modules/core/include/opencv2/core/cvstd.inl.hpp

@@ -270,6 +270,17 @@ std::ostream& operator << (std::ostream& out, const Rect_<_Tp>& rect)
     return out << "[" << rect.width << " x " << rect.height << " from (" << rect.x << ", " << rect.y << ")]";
 }
 
+static inline std::ostream& operator << (std::ostream& out, const MatSize& msize)
+{
+    int i, dims = msize.p[-1];
+    for( i = 0; i < dims; i++ )
+    {
+        out << msize.p[i];
+        if( i < dims-1 )
+            out << " x ";
+    }
+    return out;
+}
 
 #endif // OPENCV_NOSTL
 } // cv

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

@@ -1215,6 +1215,9 @@ public:
     /** @overload */
     Mat reshape(int cn, int newndims, const int* newsz) const;
 
+    /** @overload */
+    Mat reshape(int cn, const std::vector<int>& newshape) const;
+
     /** @brief Transposes a matrix.
 
     The method performs matrix transposition by means of matrix expressions. It does not perform the
@@ -1717,6 +1720,12 @@ public:
      */
     size_t total() const;
 
+    /** @brief Returns the total number of array elements.
+
+     The method returns the number of elements within a certain sub-array slice with startDim <= dim < endDim
+     */
+    size_t total(int startDim, int endDim=INT_MAX) const;
+
     //! returns N if the matrix is 1-channel (N x ptdim) or ptdim-channel (1 x N) or (N x 1); negative number otherwise
     int checkVector(int elemChannels, int depth=-1, bool requireContinuous=true) const;
 

modules/core/include/opencv2/core/mat.inl.hpp

@@ -807,6 +807,17 @@ size_t Mat::total() const
     return p;
 }
 
+inline
+size_t Mat::total(int startDim, int endDim) const
+{
+    CV_Assert( 0 <= startDim && startDim <= endDim);
+    size_t p = 1;
+    int endDim_ = endDim <= dims ? endDim : dims;
+    for( int i = startDim; i < endDim_; i++ )
+        p *= size[i];
+    return p;
+}
+
 inline
 uchar* Mat::ptr(int y)
 {

modules/core/src/matrix.cpp

@@ -1052,12 +1052,20 @@ Mat Mat::reshape(int new_cn, int new_rows) const
     int cn = channels();
     Mat hdr = *this;
 
-    if( dims > 2 && new_rows == 0 && new_cn != 0 && size[dims-1]*cn % new_cn == 0 )
+    if( dims > 2 )
     {
-        hdr.flags = (hdr.flags & ~CV_MAT_CN_MASK) | ((new_cn-1) << CV_CN_SHIFT);
+        if( new_rows == 0 && new_cn != 0 && size[dims-1]*cn % new_cn == 0 )
-        hdr.step[dims-1] = CV_ELEM_SIZE(hdr.flags);
+        {
-        hdr.size[dims-1] = hdr.size[dims-1]*cn / new_cn;
+            hdr.flags = (hdr.flags & ~CV_MAT_CN_MASK) | ((new_cn-1) << CV_CN_SHIFT);
-        return hdr;
+            hdr.step[dims-1] = CV_ELEM_SIZE(hdr.flags);
+            hdr.size[dims-1] = hdr.size[dims-1]*cn / new_cn;
+            return hdr;
+        }
+        if( new_rows > 0 )
+        {
+            int sz[] = { new_rows, (int)(total()/new_rows) };
+            return reshape(new_cn, 2, sz);
+        }
     }
 
     CV_Assert( dims <= 2 );
@@ -4482,6 +4490,18 @@ Mat Mat::reshape(int _cn, int _newndims, const int* _newsz) const
     return Mat();
 }
 
+Mat Mat::reshape(int _cn, const std::vector<int>& _newshape) const
+{
+    if(_newshape.empty())
+    {
+        CV_Assert(empty());
+        return *this;
+    }
+
+    return reshape(_cn, (int)_newshape.size(), &_newshape[0]);
+}
+
+
 NAryMatIterator::NAryMatIterator()
     : arrays(0), planes(0), ptrs(0), narrays(0), nplanes(0), size(0), iterdepth(0), idx(0)
 {