mirror of
https://github.com/opencv/opencv.git
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1020 lines
28 KiB
C++
1020 lines
28 KiB
C++
// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html
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#include "precomp.hpp"
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#include "bufferpool.impl.hpp"
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namespace cv {
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void MatAllocator::map(UMatData*, AccessFlag) const
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{
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}
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void MatAllocator::unmap(UMatData* u) const
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{
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if(u->urefcount == 0 && u->refcount == 0)
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{
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deallocate(u);
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}
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}
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void MatAllocator::download(UMatData* u, void* dstptr,
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int dims, const size_t sz[],
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const size_t srcofs[], const size_t srcstep[],
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const size_t dststep[]) const
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{
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if(!u)
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return;
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int isz[CV_MAX_DIM];
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uchar* srcptr = u->data;
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for( int i = 0; i < dims; i++ )
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{
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CV_Assert( sz[i] <= (size_t)INT_MAX );
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if( sz[i] == 0 )
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return;
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if( srcofs )
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srcptr += srcofs[i]*(i <= dims-2 ? srcstep[i] : 1);
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isz[i] = (int)sz[i];
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}
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Mat src(dims, isz, CV_8U, srcptr, srcstep);
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Mat dst(dims, isz, CV_8U, dstptr, dststep);
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const Mat* arrays[] = { &src, &dst };
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uchar* ptrs[2];
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NAryMatIterator it(arrays, ptrs, 2);
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size_t planesz = it.size;
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for( size_t j = 0; j < it.nplanes; j++, ++it )
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memcpy(ptrs[1], ptrs[0], planesz);
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}
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void MatAllocator::upload(UMatData* u, const void* srcptr, int dims, const size_t sz[],
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const size_t dstofs[], const size_t dststep[],
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const size_t srcstep[]) const
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{
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if(!u)
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return;
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int isz[CV_MAX_DIM];
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uchar* dstptr = u->data;
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for( int i = 0; i < dims; i++ )
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{
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CV_Assert( sz[i] <= (size_t)INT_MAX );
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if( sz[i] == 0 )
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return;
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if( dstofs )
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dstptr += dstofs[i]*(i <= dims-2 ? dststep[i] : 1);
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isz[i] = (int)sz[i];
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}
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Mat src(dims, isz, CV_8U, (void*)srcptr, srcstep);
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Mat dst(dims, isz, CV_8U, dstptr, dststep);
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const Mat* arrays[] = { &src, &dst };
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uchar* ptrs[2];
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NAryMatIterator it(arrays, ptrs, 2);
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size_t planesz = it.size;
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for( size_t j = 0; j < it.nplanes; j++, ++it )
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memcpy(ptrs[1], ptrs[0], planesz);
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}
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void MatAllocator::copy(UMatData* usrc, UMatData* udst, int dims, const size_t sz[],
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const size_t srcofs[], const size_t srcstep[],
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const size_t dstofs[], const size_t dststep[], bool /*sync*/) const
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{
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CV_INSTRUMENT_REGION();
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if(!usrc || !udst)
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return;
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int isz[CV_MAX_DIM];
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uchar* srcptr = usrc->data;
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uchar* dstptr = udst->data;
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for( int i = 0; i < dims; i++ )
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{
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CV_Assert( sz[i] <= (size_t)INT_MAX );
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if( sz[i] == 0 )
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return;
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if( srcofs )
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srcptr += srcofs[i]*(i <= dims-2 ? srcstep[i] : 1);
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if( dstofs )
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dstptr += dstofs[i]*(i <= dims-2 ? dststep[i] : 1);
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isz[i] = (int)sz[i];
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}
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Mat src(dims, isz, CV_8U, srcptr, srcstep);
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Mat dst(dims, isz, CV_8U, dstptr, dststep);
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const Mat* arrays[] = { &src, &dst };
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uchar* ptrs[2];
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NAryMatIterator it(arrays, ptrs, 2);
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size_t planesz = it.size;
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for( size_t j = 0; j < it.nplanes; j++, ++it )
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memcpy(ptrs[1], ptrs[0], planesz);
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}
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BufferPoolController* MatAllocator::getBufferPoolController(const char* id) const
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{
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CV_UNUSED(id);
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static DummyBufferPoolController dummy;
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return &dummy;
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}
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class StdMatAllocator CV_FINAL : public MatAllocator
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{
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public:
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UMatData* allocate(int dims, const int* sizes, int type,
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void* data0, size_t* step, AccessFlag /*flags*/, UMatUsageFlags /*usageFlags*/) const CV_OVERRIDE
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{
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size_t total = CV_ELEM_SIZE(type);
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for( int i = dims-1; i >= 0; i-- )
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{
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if( step )
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{
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if( data0 && step[i] != CV_AUTOSTEP )
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{
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CV_Assert(total <= step[i]);
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total = step[i];
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}
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else
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step[i] = total;
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}
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total *= sizes[i];
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}
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uchar* data = data0 ? (uchar*)data0 : (uchar*)fastMalloc(total);
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UMatData* u = new UMatData(this);
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u->data = u->origdata = data;
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u->size = total;
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if(data0)
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u->flags |= UMatData::USER_ALLOCATED;
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return u;
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}
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bool allocate(UMatData* u, AccessFlag /*accessFlags*/, UMatUsageFlags /*usageFlags*/) const CV_OVERRIDE
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{
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if(!u) return false;
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return true;
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}
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void deallocate(UMatData* u) const CV_OVERRIDE
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{
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if(!u)
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return;
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CV_Assert(u->urefcount == 0);
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CV_Assert(u->refcount == 0);
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if( !(u->flags & UMatData::USER_ALLOCATED) )
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{
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fastFree(u->origdata);
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u->origdata = 0;
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}
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delete u;
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}
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};
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namespace
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{
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MatAllocator* volatile g_matAllocator = NULL;
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}
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MatAllocator* Mat::getDefaultAllocator()
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{
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if (g_matAllocator == NULL)
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{
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cv::AutoLock lock(cv::getInitializationMutex());
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if (g_matAllocator == NULL)
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{
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g_matAllocator = getStdAllocator();
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}
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}
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return g_matAllocator;
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}
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void Mat::setDefaultAllocator(MatAllocator* allocator)
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{
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g_matAllocator = allocator;
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}
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MatAllocator* Mat::getStdAllocator()
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{
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CV_SINGLETON_LAZY_INIT(MatAllocator, new StdMatAllocator())
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}
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//==================================================================================================
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void setSize( Mat& m, int _dims, const int* _sz, const size_t* _steps, bool autoSteps)
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{
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CV_Assert( 0 <= _dims && _dims <= CV_MAX_DIM );
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if( m.dims != _dims )
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{
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if( m.step.p != m.step.buf )
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{
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fastFree(m.step.p);
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m.step.p = m.step.buf;
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m.size.p = &m.rows;
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}
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if( _dims > 2 )
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{
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m.step.p = (size_t*)fastMalloc(_dims*sizeof(m.step.p[0]) + (_dims+1)*sizeof(m.size.p[0]));
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m.size.p = (int*)(m.step.p + _dims) + 1;
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m.size.p[-1] = _dims;
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m.rows = m.cols = -1;
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}
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}
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m.dims = _dims;
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if( !_sz )
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return;
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size_t esz = CV_ELEM_SIZE(m.flags), esz1 = CV_ELEM_SIZE1(m.flags), total = esz;
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for( int i = _dims-1; i >= 0; i-- )
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{
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int s = _sz[i];
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CV_Assert( s >= 0 );
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m.size.p[i] = s;
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if( _steps )
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{
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if (_steps[i] % esz1 != 0)
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{
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CV_Error(Error::BadStep, "Step must be a multiple of esz1");
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}
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m.step.p[i] = i < _dims-1 ? _steps[i] : esz;
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}
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else if( autoSteps )
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{
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m.step.p[i] = total;
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int64 total1 = (int64)total*s;
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if( (uint64)total1 != (size_t)total1 )
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CV_Error( CV_StsOutOfRange, "The total matrix size does not fit to \"size_t\" type" );
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total = (size_t)total1;
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}
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}
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if( _dims == 1 )
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{
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m.dims = 2;
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m.cols = 1;
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m.step[1] = esz;
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}
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}
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int updateContinuityFlag(int flags, int dims, const int* size, const size_t* step)
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{
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int i, j;
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for( i = 0; i < dims; i++ )
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{
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if( size[i] > 1 )
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break;
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}
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uint64 t = (uint64)size[std::min(i, dims-1)]*CV_MAT_CN(flags);
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for( j = dims-1; j > i; j-- )
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{
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t *= size[j];
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if( step[j]*size[j] < step[j-1] )
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break;
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}
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if( j <= i && t == (uint64)(int)t )
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return flags | Mat::CONTINUOUS_FLAG;
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return flags & ~Mat::CONTINUOUS_FLAG;
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}
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void Mat::updateContinuityFlag()
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{
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flags = cv::updateContinuityFlag(flags, dims, size.p, step.p);
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}
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void finalizeHdr(Mat& m)
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{
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m.updateContinuityFlag();
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int d = m.dims;
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if( d > 2 )
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m.rows = m.cols = -1;
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if(m.u)
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m.datastart = m.data = m.u->data;
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if( m.data )
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{
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m.datalimit = m.datastart + m.size[0]*m.step[0];
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if( m.size[0] > 0 )
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{
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m.dataend = m.ptr() + m.size[d-1]*m.step[d-1];
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for( int i = 0; i < d-1; i++ )
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m.dataend += (m.size[i] - 1)*m.step[i];
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}
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else
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m.dataend = m.datalimit;
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}
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else
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m.dataend = m.datalimit = 0;
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}
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//==================================================================================================
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void Mat::create(int d, const int* _sizes, int _type)
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{
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int i;
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CV_Assert(0 <= d && d <= CV_MAX_DIM && _sizes);
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_type = CV_MAT_TYPE(_type);
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if( data && (d == dims || (d == 1 && dims <= 2)) && _type == type() )
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{
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if( d == 2 && rows == _sizes[0] && cols == _sizes[1] )
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return;
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for( i = 0; i < d; i++ )
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if( size[i] != _sizes[i] )
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break;
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if( i == d && (d > 1 || size[1] == 1))
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return;
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}
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int _sizes_backup[CV_MAX_DIM]; // #5991
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if (_sizes == (this->size.p))
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{
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for(i = 0; i < d; i++ )
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_sizes_backup[i] = _sizes[i];
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_sizes = _sizes_backup;
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}
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release();
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if( d == 0 )
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return;
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flags = (_type & CV_MAT_TYPE_MASK) | MAGIC_VAL;
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setSize(*this, d, _sizes, 0, true);
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if( total() > 0 )
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{
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MatAllocator *a = allocator, *a0 = getDefaultAllocator();
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#ifdef HAVE_TGPU
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if( !a || a == tegra::getAllocator() )
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a = tegra::getAllocator(d, _sizes, _type);
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#endif
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if(!a)
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a = a0;
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try
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{
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u = a->allocate(dims, size, _type, 0, step.p, ACCESS_RW /* ignored */, USAGE_DEFAULT);
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CV_Assert(u != 0);
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}
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catch (...)
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{
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if (a == a0)
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throw;
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u = a0->allocate(dims, size, _type, 0, step.p, ACCESS_RW /* ignored */, USAGE_DEFAULT);
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CV_Assert(u != 0);
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}
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CV_Assert( step[dims-1] == (size_t)CV_ELEM_SIZE(flags) );
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}
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addref();
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finalizeHdr(*this);
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}
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void Mat::create(const std::vector<int>& _sizes, int _type)
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{
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create((int)_sizes.size(), _sizes.data(), _type);
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}
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void Mat::copySize(const Mat& m)
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{
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setSize(*this, m.dims, 0, 0);
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for( int i = 0; i < dims; i++ )
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{
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size[i] = m.size[i];
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step[i] = m.step[i];
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}
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}
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void Mat::deallocate()
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{
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if(u)
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{
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UMatData* u_ = u;
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u = NULL;
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(u_->currAllocator ? u_->currAllocator : allocator ? allocator : getDefaultAllocator())->unmap(u_);
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}
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}
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Mat::Mat(const Mat& m, const Range& _rowRange, const Range& _colRange)
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: flags(MAGIC_VAL), dims(0), rows(0), cols(0), data(0), datastart(0), dataend(0),
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datalimit(0), allocator(0), u(0), size(&rows)
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{
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CV_Assert( m.dims >= 2 );
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if( m.dims > 2 )
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{
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AutoBuffer<Range> rs(m.dims);
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rs[0] = _rowRange;
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rs[1] = _colRange;
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for( int i = 2; i < m.dims; i++ )
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rs[i] = Range::all();
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*this = m(rs.data());
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return;
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}
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*this = m;
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try
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{
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if( _rowRange != Range::all() && _rowRange != Range(0,rows) )
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{
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CV_Assert( 0 <= _rowRange.start && _rowRange.start <= _rowRange.end
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&& _rowRange.end <= m.rows );
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rows = _rowRange.size();
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data += step*_rowRange.start;
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flags |= SUBMATRIX_FLAG;
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}
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if( _colRange != Range::all() && _colRange != Range(0,cols) )
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{
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CV_Assert( 0 <= _colRange.start && _colRange.start <= _colRange.end
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&& _colRange.end <= m.cols );
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cols = _colRange.size();
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data += _colRange.start*elemSize();
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flags |= SUBMATRIX_FLAG;
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}
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}
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catch(...)
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{
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release();
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throw;
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}
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updateContinuityFlag();
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if( rows <= 0 || cols <= 0 )
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{
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release();
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rows = cols = 0;
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}
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}
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Mat::Mat(const Mat& m, const Rect& roi)
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: flags(m.flags), dims(2), rows(roi.height), cols(roi.width),
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data(m.data + roi.y*m.step[0]),
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datastart(m.datastart), dataend(m.dataend), datalimit(m.datalimit),
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allocator(m.allocator), u(m.u), size(&rows)
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{
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CV_Assert( m.dims <= 2 );
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size_t esz = CV_ELEM_SIZE(flags);
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data += roi.x*esz;
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CV_Assert( 0 <= roi.x && 0 <= roi.width && roi.x + roi.width <= m.cols &&
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0 <= roi.y && 0 <= roi.height && roi.y + roi.height <= m.rows );
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if( u )
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CV_XADD(&u->refcount, 1);
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if( roi.width < m.cols || roi.height < m.rows )
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flags |= SUBMATRIX_FLAG;
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step[0] = m.step[0]; step[1] = esz;
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updateContinuityFlag();
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if( rows <= 0 || cols <= 0 )
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{
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release();
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rows = cols = 0;
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}
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}
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Mat::Mat(int _dims, const int* _sizes, int _type, void* _data, const size_t* _steps)
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: flags(MAGIC_VAL), dims(0), rows(0), cols(0), data(0), datastart(0), dataend(0),
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datalimit(0), allocator(0), u(0), size(&rows)
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{
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flags |= CV_MAT_TYPE(_type);
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datastart = data = (uchar*)_data;
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setSize(*this, _dims, _sizes, _steps, true);
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finalizeHdr(*this);
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}
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Mat::Mat(const std::vector<int>& _sizes, int _type, void* _data, const size_t* _steps)
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: flags(MAGIC_VAL), dims(0), rows(0), cols(0), data(0), datastart(0), dataend(0),
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datalimit(0), allocator(0), u(0), size(&rows)
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{
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flags |= CV_MAT_TYPE(_type);
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datastart = data = (uchar*)_data;
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setSize(*this, (int)_sizes.size(), _sizes.data(), _steps, true);
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finalizeHdr(*this);
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}
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Mat::Mat(const Mat& m, const Range* ranges)
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: flags(MAGIC_VAL), dims(0), rows(0), cols(0), data(0), datastart(0), dataend(0),
|
|
datalimit(0), allocator(0), u(0), size(&rows)
|
|
{
|
|
int d = m.dims;
|
|
|
|
CV_Assert(ranges);
|
|
for( int i = 0; i < d; i++ )
|
|
{
|
|
Range r = ranges[i];
|
|
CV_Assert( r == Range::all() || (0 <= r.start && r.start < r.end && r.end <= m.size[i]) );
|
|
}
|
|
*this = m;
|
|
for( int i = 0; i < d; i++ )
|
|
{
|
|
Range r = ranges[i];
|
|
if( r != Range::all() && r != Range(0, size.p[i]))
|
|
{
|
|
size.p[i] = r.end - r.start;
|
|
data += r.start*step.p[i];
|
|
flags |= SUBMATRIX_FLAG;
|
|
}
|
|
}
|
|
updateContinuityFlag();
|
|
}
|
|
|
|
Mat::Mat(const Mat& m, const std::vector<Range>& ranges)
|
|
: flags(MAGIC_VAL), dims(0), rows(0), cols(0), data(0), datastart(0), dataend(0),
|
|
datalimit(0), allocator(0), u(0), size(&rows)
|
|
{
|
|
int d = m.dims;
|
|
|
|
CV_Assert((int)ranges.size() == d);
|
|
for (int i = 0; i < d; i++)
|
|
{
|
|
Range r = ranges[i];
|
|
CV_Assert(r == Range::all() || (0 <= r.start && r.start < r.end && r.end <= m.size[i]));
|
|
}
|
|
*this = m;
|
|
for (int i = 0; i < d; i++)
|
|
{
|
|
Range r = ranges[i];
|
|
if (r != Range::all() && r != Range(0, size.p[i]))
|
|
{
|
|
size.p[i] = r.end - r.start;
|
|
data += r.start*step.p[i];
|
|
flags |= SUBMATRIX_FLAG;
|
|
}
|
|
}
|
|
updateContinuityFlag();
|
|
}
|
|
|
|
|
|
Mat Mat::diag(int d) const
|
|
{
|
|
CV_Assert( dims <= 2 );
|
|
Mat m = *this;
|
|
size_t esz = elemSize();
|
|
int len;
|
|
|
|
if( d >= 0 )
|
|
{
|
|
len = std::min(cols - d, rows);
|
|
m.data += esz*d;
|
|
}
|
|
else
|
|
{
|
|
len = std::min(rows + d, cols);
|
|
m.data -= step[0]*d;
|
|
}
|
|
CV_DbgAssert( len > 0 );
|
|
|
|
m.size[0] = m.rows = len;
|
|
m.size[1] = m.cols = 1;
|
|
m.step[0] += (len > 1 ? esz : 0);
|
|
|
|
m.updateContinuityFlag();
|
|
|
|
if( size() != Size(1,1) )
|
|
m.flags |= SUBMATRIX_FLAG;
|
|
|
|
return m;
|
|
}
|
|
|
|
|
|
void Mat::pop_back(size_t nelems)
|
|
{
|
|
CV_Assert( nelems <= (size_t)size.p[0] );
|
|
|
|
if( isSubmatrix() )
|
|
*this = rowRange(0, size.p[0] - (int)nelems);
|
|
else
|
|
{
|
|
size.p[0] -= (int)nelems;
|
|
dataend -= nelems*step.p[0];
|
|
}
|
|
}
|
|
|
|
|
|
void Mat::push_back_(const void* elem)
|
|
{
|
|
size_t r = size.p[0];
|
|
if( isSubmatrix() || dataend + step.p[0] > datalimit )
|
|
reserve( std::max(r + 1, (r*3+1)/2) );
|
|
|
|
size_t esz = elemSize();
|
|
memcpy(data + r*step.p[0], elem, esz);
|
|
size.p[0] = int(r + 1);
|
|
dataend += step.p[0];
|
|
uint64 tsz = size.p[0];
|
|
for( int i = 1; i < dims; i++ )
|
|
tsz *= size.p[i];
|
|
if( esz < step.p[0] || tsz != (uint64)(int)tsz )
|
|
flags &= ~CONTINUOUS_FLAG;
|
|
}
|
|
|
|
|
|
void Mat::reserve(size_t nelems)
|
|
{
|
|
const size_t MIN_SIZE = 64;
|
|
|
|
CV_Assert( (int)nelems >= 0 );
|
|
if( !isSubmatrix() && data + step.p[0]*nelems <= datalimit )
|
|
return;
|
|
|
|
int r = size.p[0];
|
|
|
|
if( (size_t)r >= nelems )
|
|
return;
|
|
|
|
size.p[0] = std::max((int)nelems, 1);
|
|
size_t newsize = total()*elemSize();
|
|
|
|
if( newsize < MIN_SIZE )
|
|
size.p[0] = (int)((MIN_SIZE + newsize - 1)*nelems/newsize);
|
|
|
|
Mat m(dims, size.p, type());
|
|
size.p[0] = r;
|
|
if( r > 0 )
|
|
{
|
|
Mat mpart = m.rowRange(0, r);
|
|
copyTo(mpart);
|
|
}
|
|
|
|
*this = m;
|
|
size.p[0] = r;
|
|
dataend = data + step.p[0]*r;
|
|
}
|
|
|
|
|
|
void Mat::reserveBuffer(size_t nbytes)
|
|
{
|
|
size_t esz = 1;
|
|
int mtype = CV_8UC1;
|
|
if (!empty())
|
|
{
|
|
if (!isSubmatrix() && data + nbytes <= dataend)//Should it be datalimit?
|
|
return;
|
|
esz = elemSize();
|
|
mtype = type();
|
|
}
|
|
|
|
size_t nelems = (nbytes - 1) / esz + 1;
|
|
|
|
#if SIZE_MAX > UINT_MAX
|
|
CV_Assert(nelems <= size_t(INT_MAX)*size_t(INT_MAX));
|
|
int newrows = nelems > size_t(INT_MAX) ? nelems > 0x400*size_t(INT_MAX) ? nelems > 0x100000 * size_t(INT_MAX) ? nelems > 0x40000000 * size_t(INT_MAX) ?
|
|
size_t(INT_MAX) : 0x40000000 : 0x100000 : 0x400 : 1;
|
|
#else
|
|
int newrows = nelems > size_t(INT_MAX) ? 2 : 1;
|
|
#endif
|
|
int newcols = (int)((nelems - 1) / newrows + 1);
|
|
|
|
create(newrows, newcols, mtype);
|
|
}
|
|
|
|
|
|
void Mat::resize(size_t nelems)
|
|
{
|
|
int saveRows = size.p[0];
|
|
if( saveRows == (int)nelems )
|
|
return;
|
|
CV_Assert( (int)nelems >= 0 );
|
|
|
|
if( isSubmatrix() || data + step.p[0]*nelems > datalimit )
|
|
reserve(nelems);
|
|
|
|
size.p[0] = (int)nelems;
|
|
dataend += (size.p[0] - saveRows)*step.p[0];
|
|
|
|
//updateContinuityFlag(*this);
|
|
}
|
|
|
|
|
|
void Mat::resize(size_t nelems, const Scalar& s)
|
|
{
|
|
int saveRows = size.p[0];
|
|
resize(nelems);
|
|
|
|
if( size.p[0] > saveRows )
|
|
{
|
|
Mat part = rowRange(saveRows, size.p[0]);
|
|
part = s;
|
|
}
|
|
}
|
|
|
|
void Mat::push_back(const Mat& elems)
|
|
{
|
|
size_t r = size.p[0];
|
|
size_t delta = elems.size.p[0];
|
|
if( delta == 0 )
|
|
return;
|
|
if( this == &elems )
|
|
{
|
|
Mat tmp = elems;
|
|
push_back(tmp);
|
|
return;
|
|
}
|
|
if( !data )
|
|
{
|
|
*this = elems.clone();
|
|
return;
|
|
}
|
|
|
|
size.p[0] = elems.size.p[0];
|
|
bool eq = size == elems.size;
|
|
size.p[0] = int(r);
|
|
if( !eq )
|
|
CV_Error(CV_StsUnmatchedSizes, "Pushed vector length is not equal to matrix row length");
|
|
if( type() != elems.type() )
|
|
CV_Error(CV_StsUnmatchedFormats, "Pushed vector type is not the same as matrix type");
|
|
|
|
if( isSubmatrix() || dataend + step.p[0]*delta > datalimit )
|
|
reserve( std::max(r + delta, (r*3+1)/2) );
|
|
|
|
size.p[0] += int(delta);
|
|
dataend += step.p[0]*delta;
|
|
|
|
//updateContinuityFlag(*this);
|
|
|
|
if( isContinuous() && elems.isContinuous() )
|
|
memcpy(data + r*step.p[0], elems.data, elems.total()*elems.elemSize());
|
|
else
|
|
{
|
|
Mat part = rowRange(int(r), int(r + delta));
|
|
elems.copyTo(part);
|
|
}
|
|
}
|
|
|
|
|
|
void Mat::locateROI( Size& wholeSize, Point& ofs ) const
|
|
{
|
|
CV_Assert( dims <= 2 && step[0] > 0 );
|
|
size_t esz = elemSize(), minstep;
|
|
ptrdiff_t delta1 = data - datastart, delta2 = dataend - datastart;
|
|
|
|
if( delta1 == 0 )
|
|
ofs.x = ofs.y = 0;
|
|
else
|
|
{
|
|
ofs.y = (int)(delta1/step[0]);
|
|
ofs.x = (int)((delta1 - step[0]*ofs.y)/esz);
|
|
CV_DbgAssert( data == datastart + ofs.y*step[0] + ofs.x*esz );
|
|
}
|
|
minstep = (ofs.x + cols)*esz;
|
|
wholeSize.height = (int)((delta2 - minstep)/step[0] + 1);
|
|
wholeSize.height = std::max(wholeSize.height, ofs.y + rows);
|
|
wholeSize.width = (int)((delta2 - step*(wholeSize.height-1))/esz);
|
|
wholeSize.width = std::max(wholeSize.width, ofs.x + cols);
|
|
}
|
|
|
|
Mat& Mat::adjustROI( int dtop, int dbottom, int dleft, int dright )
|
|
{
|
|
CV_Assert( dims <= 2 && step[0] > 0 );
|
|
Size wholeSize; Point ofs;
|
|
size_t esz = elemSize();
|
|
locateROI( wholeSize, ofs );
|
|
int row1 = std::min(std::max(ofs.y - dtop, 0), wholeSize.height), row2 = std::max(0, std::min(ofs.y + rows + dbottom, wholeSize.height));
|
|
int col1 = std::min(std::max(ofs.x - dleft, 0), wholeSize.width), col2 = std::max(0, std::min(ofs.x + cols + dright, wholeSize.width));
|
|
if(row1 > row2)
|
|
std::swap(row1, row2);
|
|
if(col1 > col2)
|
|
std::swap(col1, col2);
|
|
|
|
data += (row1 - ofs.y)*step + (col1 - ofs.x)*esz;
|
|
rows = row2 - row1; cols = col2 - col1;
|
|
size.p[0] = rows; size.p[1] = cols;
|
|
updateContinuityFlag();
|
|
return *this;
|
|
}
|
|
|
|
Mat Mat::reshape(int new_cn, int new_rows) const
|
|
{
|
|
int cn = channels();
|
|
Mat hdr = *this;
|
|
|
|
if( dims > 2 )
|
|
{
|
|
if( new_rows == 0 && new_cn != 0 && size[dims-1]*cn % new_cn == 0 )
|
|
{
|
|
hdr.flags = (hdr.flags & ~CV_MAT_CN_MASK) | ((new_cn-1) << CV_CN_SHIFT);
|
|
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 );
|
|
|
|
if( new_cn == 0 )
|
|
new_cn = cn;
|
|
|
|
int total_width = cols * cn;
|
|
|
|
if( (new_cn > total_width || total_width % new_cn != 0) && new_rows == 0 )
|
|
new_rows = rows * total_width / new_cn;
|
|
|
|
if( new_rows != 0 && new_rows != rows )
|
|
{
|
|
int total_size = total_width * rows;
|
|
if( !isContinuous() )
|
|
CV_Error( CV_BadStep,
|
|
"The matrix is not continuous, thus its number of rows can not be changed" );
|
|
|
|
if( (unsigned)new_rows > (unsigned)total_size )
|
|
CV_Error( CV_StsOutOfRange, "Bad new number of rows" );
|
|
|
|
total_width = total_size / new_rows;
|
|
|
|
if( total_width * new_rows != total_size )
|
|
CV_Error( CV_StsBadArg, "The total number of matrix elements "
|
|
"is not divisible by the new number of rows" );
|
|
|
|
hdr.rows = new_rows;
|
|
hdr.step[0] = total_width * elemSize1();
|
|
}
|
|
|
|
int new_width = total_width / new_cn;
|
|
|
|
if( new_width * new_cn != total_width )
|
|
CV_Error( CV_BadNumChannels,
|
|
"The total width is not divisible by the new number of channels" );
|
|
|
|
hdr.cols = new_width;
|
|
hdr.flags = (hdr.flags & ~CV_MAT_CN_MASK) | ((new_cn-1) << CV_CN_SHIFT);
|
|
hdr.step[1] = CV_ELEM_SIZE(hdr.flags);
|
|
return hdr;
|
|
}
|
|
|
|
Mat Mat::reshape(int _cn, int _newndims, const int* _newsz) const
|
|
{
|
|
if(_newndims == dims)
|
|
{
|
|
if(_newsz == 0)
|
|
return reshape(_cn);
|
|
if(_newndims == 2)
|
|
return reshape(_cn, _newsz[0]);
|
|
}
|
|
|
|
if (isContinuous())
|
|
{
|
|
CV_Assert(_cn >= 0 && _newndims > 0 && _newndims <= CV_MAX_DIM && _newsz);
|
|
|
|
if (_cn == 0)
|
|
_cn = this->channels();
|
|
else
|
|
CV_Assert(_cn <= CV_CN_MAX);
|
|
|
|
size_t total_elem1_ref = this->total() * this->channels();
|
|
size_t total_elem1 = _cn;
|
|
|
|
AutoBuffer<int, 4> newsz_buf( (size_t)_newndims );
|
|
|
|
for (int i = 0; i < _newndims; i++)
|
|
{
|
|
CV_Assert(_newsz[i] >= 0);
|
|
|
|
if (_newsz[i] > 0)
|
|
newsz_buf[i] = _newsz[i];
|
|
else if (i < dims)
|
|
newsz_buf[i] = this->size[i];
|
|
else
|
|
CV_Error(CV_StsOutOfRange, "Copy dimension (which has zero size) is not present in source matrix");
|
|
|
|
total_elem1 *= (size_t)newsz_buf[i];
|
|
}
|
|
|
|
if (total_elem1 != total_elem1_ref)
|
|
CV_Error(CV_StsUnmatchedSizes, "Requested and source matrices have different count of elements");
|
|
|
|
Mat hdr = *this;
|
|
hdr.flags = (hdr.flags & ~CV_MAT_CN_MASK) | ((_cn-1) << CV_CN_SHIFT);
|
|
setSize(hdr, _newndims, newsz_buf.data(), NULL, true);
|
|
|
|
return hdr;
|
|
}
|
|
|
|
CV_Error(CV_StsNotImplemented, "Reshaping of n-dimensional non-continuous matrices is not supported yet");
|
|
// TBD
|
|
}
|
|
|
|
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]);
|
|
}
|
|
|
|
Mat Mat::diag(const Mat& d)
|
|
{
|
|
CV_Assert( d.cols == 1 || d.rows == 1 );
|
|
int len = d.rows + d.cols - 1;
|
|
Mat m(len, len, d.type(), Scalar(0));
|
|
Mat md = m.diag();
|
|
if( d.cols == 1 )
|
|
d.copyTo(md);
|
|
else
|
|
transpose(d, md);
|
|
return m;
|
|
}
|
|
|
|
int Mat::checkVector(int _elemChannels, int _depth, bool _requireContinuous) const
|
|
{
|
|
return data && (depth() == _depth || _depth <= 0) &&
|
|
(isContinuous() || !_requireContinuous) &&
|
|
((dims == 2 && (((rows == 1 || cols == 1) && channels() == _elemChannels) ||
|
|
(cols == _elemChannels && channels() == 1))) ||
|
|
(dims == 3 && channels() == 1 && size.p[2] == _elemChannels && (size.p[0] == 1 || size.p[1] == 1) &&
|
|
(isContinuous() || step.p[1] == step.p[2]*size.p[2])))
|
|
? (int)(total()*channels()/_elemChannels) : -1;
|
|
}
|
|
|
|
|
|
static inline Size getContinuousSize_(int flags, int cols, int rows, int widthScale)
|
|
{
|
|
int64 sz = (int64)cols * rows * widthScale;
|
|
bool has_int_overflow = sz >= INT_MAX;
|
|
bool isContiguous = (flags & Mat::CONTINUOUS_FLAG) != 0;
|
|
return (isContiguous && !has_int_overflow)
|
|
? Size((int)sz, 1)
|
|
: Size(cols * widthScale, rows);
|
|
}
|
|
|
|
Size getContinuousSize2D(Mat& m1, int widthScale)
|
|
{
|
|
CV_CheckLE(m1.dims, 2, "");
|
|
return getContinuousSize_(m1.flags,
|
|
m1.cols, m1.rows, widthScale);
|
|
}
|
|
Size getContinuousSize2D(Mat& m1, Mat& m2, int widthScale)
|
|
{
|
|
CV_CheckLE(m1.dims, 2, "");
|
|
CV_CheckLE(m2.dims, 2, "");
|
|
const Size sz1 = m1.size();
|
|
if (sz1 != m2.size()) // reshape all matrixes to the same size (#4159)
|
|
{
|
|
size_t total_sz = m1.total();
|
|
CV_CheckEQ(total_sz, m2.total(), "");
|
|
bool is_m1_vector = m1.cols == 1 || m1.rows == 1;
|
|
bool is_m2_vector = m2.cols == 1 || m2.rows == 1;
|
|
CV_Assert(is_m1_vector); CV_Assert(is_m2_vector);
|
|
int total = (int)total_sz; // vector-column
|
|
bool isContiguous = ((m1.flags & m2.flags) & Mat::CONTINUOUS_FLAG) != 0;
|
|
bool has_int_overflow = ((int64)total_sz * widthScale) >= INT_MAX;
|
|
if (isContiguous && !has_int_overflow)
|
|
total = 1; // vector-row
|
|
m1 = m1.reshape(0, total);
|
|
m2 = m2.reshape(0, total);
|
|
CV_Assert(m1.cols == m2.cols && m1.rows == m2.rows);
|
|
return Size(m1.cols * widthScale, m1.rows);
|
|
}
|
|
return getContinuousSize_(m1.flags & m2.flags,
|
|
m1.cols, m1.rows, widthScale);
|
|
}
|
|
|
|
Size getContinuousSize2D(Mat& m1, Mat& m2, Mat& m3, int widthScale)
|
|
{
|
|
CV_CheckLE(m1.dims, 2, "");
|
|
CV_CheckLE(m2.dims, 2, "");
|
|
CV_CheckLE(m3.dims, 2, "");
|
|
const Size sz1 = m1.size();
|
|
if (sz1 != m2.size() || sz1 != m3.size()) // reshape all matrixes to the same size (#4159)
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{
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size_t total_sz = m1.total();
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CV_CheckEQ(total_sz, m2.total(), "");
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CV_CheckEQ(total_sz, m3.total(), "");
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bool is_m1_vector = m1.cols == 1 || m1.rows == 1;
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bool is_m2_vector = m2.cols == 1 || m2.rows == 1;
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bool is_m3_vector = m3.cols == 1 || m3.rows == 1;
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CV_Assert(is_m1_vector); CV_Assert(is_m2_vector); CV_Assert(is_m3_vector);
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int total = (int)total_sz; // vector-column
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bool isContiguous = ((m1.flags & m2.flags & m3.flags) & Mat::CONTINUOUS_FLAG) != 0;
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bool has_int_overflow = ((int64)total_sz * widthScale) >= INT_MAX;
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if (isContiguous && !has_int_overflow)
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total = 1; // vector-row
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m1 = m1.reshape(0, total);
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m2 = m2.reshape(0, total);
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m3 = m3.reshape(0, total);
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CV_Assert(m1.cols == m2.cols && m1.rows == m2.rows && m1.cols == m3.cols && m1.rows == m3.rows);
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return Size(m1.cols * widthScale, m1.rows);
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}
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return getContinuousSize_(m1.flags & m2.flags & m3.flags,
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m1.cols, m1.rows, widthScale);
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}
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|
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} // cv::
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