/*M/////////////////////////////////////////////////////////////////////////////////////// // // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. // // By downloading, copying, installing or using the software you agree to this license. // If you do not agree to this license, do not download, install, // copy or use the software. // // // License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2000-2008, Intel Corporation, all rights reserved. // Copyright (C) 2009, Willow Garage Inc., all rights reserved. // Third party copyrights are property of their respective owners. // // Redistribution and use in source and binary forms, with or without modification, // are permitted provided that the following conditions are met: // // * Redistribution's of source code must retain the above copyright notice, // this list of conditions and the following disclaimer. // // * Redistribution's in binary form must reproduce the above copyright notice, // this list of conditions and the following disclaimer in the documentation // and/or other materials provided with the distribution. // // * The name of the copyright holders may not be used to endorse or promote products // derived from this software without specific prior written permission. // // This software is provided by the copyright holders and contributors "as is" and // any express or implied warranties, including, but not limited to, the implied // warranties of merchantability and fitness for a particular purpose are disclaimed. // In no event shall the Intel Corporation or contributors be liable for any direct, // indirect, incidental, special, exemplary, or consequential damages // (including, but not limited to, procurement of substitute goods or services; // loss of use, data, or profits; or business interruption) however caused // and on any theory of liability, whether in contract, strict liability, // or tort (including negligence or otherwise) arising in any way out of // the use of this software, even if advised of the possibility of such damage. // //M*/ #include "precomp.hpp" #include "opencl_kernels.hpp" ///////////////////////////////// UMat implementation /////////////////////////////// namespace cv { // it should be a prime number for the best hash function enum { UMAT_NLOCKS = 31 }; static Mutex umatLocks[UMAT_NLOCKS]; UMatData::UMatData(const MatAllocator* allocator) { prevAllocator = currAllocator = allocator; urefcount = refcount = 0; data = origdata = 0; size = 0; flags = 0; handle = 0; userdata = 0; } void UMatData::lock() { umatLocks[(size_t)(void*)this % UMAT_NLOCKS].lock(); } void UMatData::unlock() { umatLocks[(size_t)(void*)this % UMAT_NLOCKS].unlock(); } MatAllocator* UMat::getStdAllocator() { return ocl::getOpenCLAllocator(); } void swap( UMat& a, UMat& b ) { std::swap(a.flags, b.flags); std::swap(a.dims, b.dims); std::swap(a.rows, b.rows); std::swap(a.cols, b.cols); std::swap(a.allocator, b.allocator); std::swap(a.u, b.u); std::swap(a.offset, b.offset); std::swap(a.size.p, b.size.p); std::swap(a.step.p, b.step.p); std::swap(a.step.buf[0], b.step.buf[0]); std::swap(a.step.buf[1], b.step.buf[1]); if( a.step.p == b.step.buf ) { a.step.p = a.step.buf; a.size.p = &a.rows; } if( b.step.p == a.step.buf ) { b.step.p = b.step.buf; b.size.p = &b.rows; } } static inline void setSize( UMat& m, int _dims, const int* _sz, const size_t* _steps, bool autoSteps=false ) { CV_Assert( 0 <= _dims && _dims <= CV_MAX_DIM ); if( m.dims != _dims ) { if( m.step.p != m.step.buf ) { fastFree(m.step.p); m.step.p = m.step.buf; m.size.p = &m.rows; } if( _dims > 2 ) { m.step.p = (size_t*)fastMalloc(_dims*sizeof(m.step.p[0]) + (_dims+1)*sizeof(m.size.p[0])); m.size.p = (int*)(m.step.p + _dims) + 1; m.size.p[-1] = _dims; m.rows = m.cols = -1; } } m.dims = _dims; if( !_sz ) return; size_t esz = CV_ELEM_SIZE(m.flags), total = esz; int i; for( i = _dims-1; i >= 0; i-- ) { int s = _sz[i]; CV_Assert( s >= 0 ); m.size.p[i] = s; if( _steps ) m.step.p[i] = i < _dims-1 ? _steps[i] : esz; else if( autoSteps ) { m.step.p[i] = total; int64 total1 = (int64)total*s; if( (uint64)total1 != (size_t)total1 ) CV_Error( CV_StsOutOfRange, "The total matrix size does not fit to \"size_t\" type" ); total = (size_t)total1; } } if( _dims == 1 ) { m.dims = 2; m.cols = 1; m.step[1] = esz; } } static void updateContinuityFlag(UMat& m) { int i, j; for( i = 0; i < m.dims; i++ ) { if( m.size[i] > 1 ) break; } for( j = m.dims-1; j > i; j-- ) { if( m.step[j]*m.size[j] < m.step[j-1] ) break; } uint64 total = (uint64)m.step[0]*m.size[0]; if( j <= i && total == (size_t)total ) m.flags |= UMat::CONTINUOUS_FLAG; else m.flags &= ~UMat::CONTINUOUS_FLAG; } static void finalizeHdr(UMat& m) { updateContinuityFlag(m); int d = m.dims; if( d > 2 ) m.rows = m.cols = -1; } UMat Mat::getUMat(int accessFlags) const { UMat hdr; if(!u) return hdr; UMat::getStdAllocator()->allocate(u, accessFlags); hdr.flags = flags; setSize(hdr, dims, size.p, step.p); finalizeHdr(hdr); hdr.u = u; hdr.offset = data - datastart; return hdr; } void UMat::create(int d, const int* _sizes, int _type) { int i; CV_Assert(0 <= d && d <= CV_MAX_DIM && _sizes); _type = CV_MAT_TYPE(_type); if( u && (d == dims || (d == 1 && dims <= 2)) && _type == type() ) { if( d == 2 && rows == _sizes[0] && cols == _sizes[1] ) return; for( i = 0; i < d; i++ ) if( size[i] != _sizes[i] ) break; if( i == d && (d > 1 || size[1] == 1)) return; } release(); if( d == 0 ) return; flags = (_type & CV_MAT_TYPE_MASK) | MAGIC_VAL; setSize(*this, d, _sizes, 0, true); offset = 0; if( total() > 0 ) { MatAllocator *a = allocator, *a0 = getStdAllocator(); if(!a) a = a0; try { u = a->allocate(dims, size, _type, step.p); CV_Assert(u != 0); } catch(...) { if(a != a0) u = a0->allocate(dims, size, _type, step.p); CV_Assert(u != 0); } CV_Assert( step[dims-1] == (size_t)CV_ELEM_SIZE(flags) ); } finalizeHdr(*this); } void UMat::copySize(const UMat& m) { setSize(*this, m.dims, 0, 0); for( int i = 0; i < dims; i++ ) { size[i] = m.size[i]; step[i] = m.step[i]; } } void UMat::deallocate() { u->currAllocator->deallocate(u); } UMat::UMat(const UMat& m, const Range& _rowRange, const Range& _colRange) : flags(MAGIC_VAL), dims(0), rows(0), cols(0), allocator(0), u(0), offset(0), size(&rows) { CV_Assert( m.dims >= 2 ); if( m.dims > 2 ) { AutoBuffer rs(m.dims); rs[0] = _rowRange; rs[1] = _colRange; for( int i = 2; i < m.dims; i++ ) rs[i] = Range::all(); *this = m(rs); return; } *this = m; if( _rowRange != Range::all() && _rowRange != Range(0,rows) ) { CV_Assert( 0 <= _rowRange.start && _rowRange.start <= _rowRange.end && _rowRange.end <= m.rows ); rows = _rowRange.size(); offset += step*_rowRange.start; flags |= SUBMATRIX_FLAG; } if( _colRange != Range::all() && _colRange != Range(0,cols) ) { CV_Assert( 0 <= _colRange.start && _colRange.start <= _colRange.end && _colRange.end <= m.cols ); cols = _colRange.size(); offset += _colRange.start*elemSize(); flags &= cols < m.cols ? ~CONTINUOUS_FLAG : -1; flags |= SUBMATRIX_FLAG; } if( rows == 1 ) flags |= CONTINUOUS_FLAG; if( rows <= 0 || cols <= 0 ) { release(); rows = cols = 0; } } UMat::UMat(const UMat& m, const Rect& roi) : flags(m.flags), dims(2), rows(roi.height), cols(roi.width), allocator(m.allocator), u(m.u), offset(m.offset + roi.y*m.step[0]), size(&rows) { CV_Assert( m.dims <= 2 ); flags &= roi.width < m.cols ? ~CONTINUOUS_FLAG : -1; flags |= roi.height == 1 ? CONTINUOUS_FLAG : 0; size_t esz = CV_ELEM_SIZE(flags); offset += roi.x*esz; CV_Assert( 0 <= roi.x && 0 <= roi.width && roi.x + roi.width <= m.cols && 0 <= roi.y && 0 <= roi.height && roi.y + roi.height <= m.rows ); if( u ) CV_XADD(&(u->urefcount), 1); if( roi.width < m.cols || roi.height < m.rows ) flags |= SUBMATRIX_FLAG; step[0] = m.step[0]; step[1] = esz; if( rows <= 0 || cols <= 0 ) { release(); rows = cols = 0; } } UMat::UMat(const UMat& m, const Range* ranges) : flags(MAGIC_VAL), dims(0), rows(0), cols(0), allocator(0), u(0), offset(0), size(&rows) { int i, d = m.dims; CV_Assert(ranges); for( 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( 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; offset += r.start*step.p[i]; flags |= SUBMATRIX_FLAG; } } updateContinuityFlag(*this); } UMat UMat::diag(int d) const { CV_Assert( dims <= 2 ); UMat m = *this; size_t esz = elemSize(); int len; if( d >= 0 ) { len = std::min(cols - d, rows); m.offset += esz*d; } else { len = std::min(rows + d, cols); m.offset -= 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); if( m.rows > 1 ) m.flags &= ~CONTINUOUS_FLAG; else m.flags |= CONTINUOUS_FLAG; if( size() != Size(1,1) ) m.flags |= SUBMATRIX_FLAG; return m; } void UMat::locateROI( Size& wholeSize, Point& ofs ) const { CV_Assert( dims <= 2 && step[0] > 0 ); size_t esz = elemSize(), minstep; ptrdiff_t delta1 = (ptrdiff_t)offset, delta2 = (ptrdiff_t)u->size; 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( offset == (size_t)(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); } UMat& UMat::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::max(ofs.y - dtop, 0), row2 = std::min(ofs.y + rows + dbottom, wholeSize.height); int col1 = std::max(ofs.x - dleft, 0), col2 = std::min(ofs.x + cols + dright, wholeSize.width); offset += (row1 - ofs.y)*step + (col1 - ofs.x)*esz; rows = row2 - row1; cols = col2 - col1; size.p[0] = rows; size.p[1] = cols; if( esz*cols == step[0] || rows == 1 ) flags |= CONTINUOUS_FLAG; else flags &= ~CONTINUOUS_FLAG; return *this; } UMat UMat::reshape(int new_cn, int new_rows) const { int cn = channels(); UMat hdr = *this; if( dims > 2 && 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; } 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; } UMat UMat::diag(const UMat& d) { CV_Assert( d.cols == 1 || d.rows == 1 ); int len = d.rows + d.cols - 1; UMat m(len, len, d.type(), Scalar(0)); UMat md = m.diag(); if( d.cols == 1 ) d.copyTo(md); else transpose(d, md); return m; } int UMat::checkVector(int _elemChannels, int _depth, bool _requireContinuous) const { return (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; } UMat UMat::cross(InputArray) const { CV_Error(CV_StsNotImplemented, ""); return UMat(); } UMat UMat::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]); } CV_Error(CV_StsNotImplemented, ""); // TBD return UMat(); } Mat UMat::getMat(int accessFlags) const { if(!u) return Mat(); u->currAllocator->map(u, accessFlags); CV_Assert(u->data != 0); Mat hdr(dims, size.p, type(), u->data + offset, step.p); hdr.u = u; hdr.datastart = u->data; hdr.data = hdr.datastart + offset; hdr.datalimit = hdr.dataend = u->data + u->size; CV_XADD(&hdr.u->refcount, 1); return hdr; } void* UMat::handle(int /*accessFlags*/) const { if( !u ) return 0; // check flags: if CPU copy is newer, copy it back to GPU. if( u->deviceCopyObsolete() ) { CV_Assert(u->refcount == 0); u->currAllocator->unmap(u); } /*else if( u->refcount > 0 && (accessFlags & ACCESS_WRITE) ) { CV_Error(Error::StsError, "it's not allowed to access UMat handle for writing " "while it's mapped; call Mat::release() first for all its mappings"); }*/ return u->handle; } void UMat::ndoffset(size_t* ofs) const { // offset = step[0]*ofs[0] + step[1]*ofs[1] + step[2]*ofs[2] + ...; size_t val = offset; for( int i = 0; i < dims; i++ ) { size_t s = step.p[i]; ofs[i] = val / s; val -= ofs[i]*s; } } void UMat::copyTo(OutputArray _dst) const { int dtype = _dst.type(); if( _dst.fixedType() && dtype != type() ) { CV_Assert( channels() == CV_MAT_CN(dtype) ); convertTo( _dst, dtype ); return; } if( empty() ) { _dst.release(); return; } size_t i, sz[CV_MAX_DIM], srcofs[CV_MAX_DIM], dstofs[CV_MAX_DIM], esz = elemSize(); for( i = 0; i < (size_t)dims; i++ ) sz[i] = size.p[i]; sz[dims-1] *= esz; ndoffset(srcofs); srcofs[dims-1] *= esz; _dst.create( dims, size.p, type() ); if( _dst.kind() == _InputArray::UMAT ) { UMat dst = _dst.getUMat(); void* srchandle = handle(ACCESS_READ); void* dsthandle = dst.handle(ACCESS_WRITE); if( srchandle == dsthandle && dst.offset == offset ) return; dst.ndoffset(dstofs); CV_Assert(u->currAllocator == dst.u->currAllocator); u->currAllocator->copy(u, dst.u, dims, sz, srcofs, step.p, dstofs, dst.step.p, false); } else { Mat dst = _dst.getMat(); u->currAllocator->download(u, dst.data, dims, sz, srcofs, step.p, dst.step.p); } } void UMat::convertTo(OutputArray, int, double, double) const { CV_Error(Error::StsNotImplemented, ""); } UMat& UMat::setTo(InputArray _value, InputArray _mask) { bool haveMask = !_mask.empty(); int tp = type(), cn = CV_MAT_CN(tp); if( dims <= 2 && cn <= 4 && ocl::useOpenCL() ) { Mat value = _value.getMat(); CV_Assert( checkScalar(value, type(), _value.kind(), _InputArray::UMAT) ); double buf[4]; convertAndUnrollScalar(value, tp, (uchar*)buf, 1); char opts[1024]; sprintf(opts, "-D dstT=%s", ocl::memopTypeToStr(tp)); ocl::Kernel setK(haveMask ? "setMask" : "set", ocl::core::copyset_oclsrc, opts); if( !setK.empty() ) { ocl::KernelArg scalararg(0, 0, 0, buf, CV_ELEM_SIZE(tp)); UMat mask; if( haveMask ) { mask = _mask.getUMat(); CV_Assert( mask.size() == size() && mask.type() == CV_8U ); ocl::KernelArg maskarg = ocl::KernelArg::ReadOnlyNoSize(mask); ocl::KernelArg dstarg = ocl::KernelArg::ReadWrite(*this); setK.args(maskarg, dstarg, scalararg); } else { ocl::KernelArg dstarg = ocl::KernelArg::WriteOnly(*this); setK.args(dstarg, scalararg); } size_t globalsize[] = { cols, rows }; if( setK.run(2, globalsize, 0, false) ) return *this; } } Mat m = getMat(haveMask ? ACCESS_RW : ACCESS_WRITE); m.setTo(_value, _mask); return *this; } UMat& UMat::operator = (const Scalar&) { CV_Error(Error::StsNotImplemented, ""); return *this; } } /* End of file. */