/*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" using namespace cv; using namespace cv::cuda; #if !defined (HAVE_CUDA) || defined (CUDA_DISABLER) void cv::cuda::StereoConstantSpaceBP::estimateRecommendedParams(int, int, int&, int&, int&, int&) { throw_no_cuda(); } Ptr cv::cuda::createStereoConstantSpaceBP(int, int, int, int, int) { throw_no_cuda(); return Ptr(); } #else /* !defined (HAVE_CUDA) */ #include "cuda/stereocsbp.hpp" namespace { class StereoCSBPImpl : public cuda::StereoConstantSpaceBP { public: StereoCSBPImpl(int ndisp, int iters, int levels, int nr_plane, int msg_type); void compute(InputArray left, InputArray right, OutputArray disparity); void compute(InputArray left, InputArray right, OutputArray disparity, Stream& stream); void compute(InputArray data, OutputArray disparity, Stream& stream); int getMinDisparity() const { return min_disp_th_; } void setMinDisparity(int minDisparity) { min_disp_th_ = minDisparity; } int getNumDisparities() const { return ndisp_; } void setNumDisparities(int numDisparities) { ndisp_ = numDisparities; } int getBlockSize() const { return 0; } void setBlockSize(int /*blockSize*/) {} int getSpeckleWindowSize() const { return 0; } void setSpeckleWindowSize(int /*speckleWindowSize*/) {} int getSpeckleRange() const { return 0; } void setSpeckleRange(int /*speckleRange*/) {} int getDisp12MaxDiff() const { return 0; } void setDisp12MaxDiff(int /*disp12MaxDiff*/) {} int getNumIters() const { return iters_; } void setNumIters(int iters) { iters_ = iters; } int getNumLevels() const { return levels_; } void setNumLevels(int levels) { levels_ = levels; } double getMaxDataTerm() const { return max_data_term_; } void setMaxDataTerm(double max_data_term) { max_data_term_ = (float) max_data_term; } double getDataWeight() const { return data_weight_; } void setDataWeight(double data_weight) { data_weight_ = (float) data_weight; } double getMaxDiscTerm() const { return max_disc_term_; } void setMaxDiscTerm(double max_disc_term) { max_disc_term_ = (float) max_disc_term; } double getDiscSingleJump() const { return disc_single_jump_; } void setDiscSingleJump(double disc_single_jump) { disc_single_jump_ = (float) disc_single_jump; } int getMsgType() const { return msg_type_; } void setMsgType(int msg_type) { msg_type_ = msg_type; } int getNrPlane() const { return nr_plane_; } void setNrPlane(int nr_plane) { nr_plane_ = nr_plane; } bool getUseLocalInitDataCost() const { return use_local_init_data_cost_; } void setUseLocalInitDataCost(bool use_local_init_data_cost) { use_local_init_data_cost_ = use_local_init_data_cost; } private: int min_disp_th_; int ndisp_; int iters_; int levels_; float max_data_term_; float data_weight_; float max_disc_term_; float disc_single_jump_; int msg_type_; int nr_plane_; bool use_local_init_data_cost_; GpuMat mbuf_; GpuMat temp_; GpuMat outBuf_; }; const float DEFAULT_MAX_DATA_TERM = 30.0f; const float DEFAULT_DATA_WEIGHT = 1.0f; const float DEFAULT_MAX_DISC_TERM = 160.0f; const float DEFAULT_DISC_SINGLE_JUMP = 10.0f; StereoCSBPImpl::StereoCSBPImpl(int ndisp, int iters, int levels, int nr_plane, int msg_type) : min_disp_th_(0), ndisp_(ndisp), iters_(iters), levels_(levels), max_data_term_(DEFAULT_MAX_DATA_TERM), data_weight_(DEFAULT_DATA_WEIGHT), max_disc_term_(DEFAULT_MAX_DISC_TERM), disc_single_jump_(DEFAULT_DISC_SINGLE_JUMP), msg_type_(msg_type), nr_plane_(nr_plane), use_local_init_data_cost_(true) { } void StereoCSBPImpl::compute(InputArray left, InputArray right, OutputArray disparity) { compute(left, right, disparity, Stream::Null()); } void StereoCSBPImpl::compute(InputArray _left, InputArray _right, OutputArray disp, Stream& _stream) { using namespace cv::cuda::device::stereocsbp; CV_Assert( msg_type_ == CV_32F || msg_type_ == CV_16S ); CV_Assert( 0 < ndisp_ && 0 < iters_ && 0 < levels_ && 0 < nr_plane_ && levels_ <= 8 ); GpuMat left = _left.getGpuMat(); GpuMat right = _right.getGpuMat(); CV_Assert( left.type() == CV_8UC1 || left.type() == CV_8UC3 || left.type() == CV_8UC4 ); CV_Assert( left.size() == right.size() && left.type() == right.type() ); cudaStream_t stream = StreamAccessor::getStream(_stream); //////////////////////////////////////////////////////////////////////////////////////////// // Init int rows = left.rows; int cols = left.cols; levels_ = std::min(levels_, int(log((double)ndisp_) / log(2.0))); // compute sizes AutoBuffer buf(levels_ * 3); int* cols_pyr = buf; int* rows_pyr = cols_pyr + levels_; int* nr_plane_pyr = rows_pyr + levels_; cols_pyr[0] = cols; rows_pyr[0] = rows; nr_plane_pyr[0] = nr_plane_; for (int i = 1; i < levels_; i++) { cols_pyr[i] = cols_pyr[i-1] / 2; rows_pyr[i] = rows_pyr[i-1] / 2; nr_plane_pyr[i] = nr_plane_pyr[i-1] * 2; } GpuMat u[2], d[2], l[2], r[2], disp_selected_pyr[2], data_cost, data_cost_selected; //allocate buffers int buffers_count = 10; // (up + down + left + right + disp_selected_pyr) * 2 buffers_count += 2; // data_cost has twice more rows than other buffers, what's why +2, not +1; buffers_count += 1; // data_cost_selected mbuf_.create(rows * nr_plane_ * buffers_count, cols, msg_type_); data_cost = mbuf_.rowRange(0, rows * nr_plane_ * 2); data_cost_selected = mbuf_.rowRange(data_cost.rows, data_cost.rows + rows * nr_plane_); for(int k = 0; k < 2; ++k) // in/out { GpuMat sub1 = mbuf_.rowRange(data_cost.rows + data_cost_selected.rows, mbuf_.rows); GpuMat sub2 = sub1.rowRange((k+0)*sub1.rows/2, (k+1)*sub1.rows/2); GpuMat *buf_ptrs[] = { &u[k], &d[k], &l[k], &r[k], &disp_selected_pyr[k] }; for(int _r = 0; _r < 5; ++_r) { *buf_ptrs[_r] = sub2.rowRange(_r * sub2.rows/5, (_r+1) * sub2.rows/5); CV_DbgAssert( buf_ptrs[_r]->cols == cols && buf_ptrs[_r]->rows == rows * nr_plane_ ); } }; size_t elem_step = mbuf_.step / mbuf_.elemSize(); Size temp_size = data_cost.size(); if ((size_t)temp_size.area() < elem_step * rows_pyr[levels_ - 1] * ndisp_) temp_size = Size(static_cast(elem_step), rows_pyr[levels_ - 1] * ndisp_); temp_.create(temp_size, msg_type_); //////////////////////////////////////////////////////////////////////////// // Compute l[0].setTo(0, _stream); d[0].setTo(0, _stream); r[0].setTo(0, _stream); u[0].setTo(0, _stream); l[1].setTo(0, _stream); d[1].setTo(0, _stream); r[1].setTo(0, _stream); u[1].setTo(0, _stream); data_cost.setTo(0, _stream); data_cost_selected.setTo(0, _stream); int cur_idx = 0; if (msg_type_ == CV_32F) { for (int i = levels_ - 1; i >= 0; i--) { if (i == levels_ - 1) { init_data_cost(left.ptr(), right.ptr(), temp_.ptr(), left.step, left.rows, left.cols, disp_selected_pyr[cur_idx].ptr(), data_cost_selected.ptr(), elem_step, rows_pyr[i], cols_pyr[i], i, nr_plane_pyr[i], ndisp_, left.channels(), data_weight_, max_data_term_, min_disp_th_, use_local_init_data_cost_, stream); } else { compute_data_cost(left.ptr(), right.ptr(), left.step, disp_selected_pyr[cur_idx].ptr(), data_cost.ptr(), elem_step, left.rows, left.cols, rows_pyr[i], cols_pyr[i], rows_pyr[i+1], i, nr_plane_pyr[i+1], left.channels(), data_weight_, max_data_term_, min_disp_th_, stream); int new_idx = (cur_idx + 1) & 1; init_message(temp_.ptr(), u[new_idx].ptr(), d[new_idx].ptr(), l[new_idx].ptr(), r[new_idx].ptr(), u[cur_idx].ptr(), d[cur_idx].ptr(), l[cur_idx].ptr(), r[cur_idx].ptr(), disp_selected_pyr[new_idx].ptr(), disp_selected_pyr[cur_idx].ptr(), data_cost_selected.ptr(), data_cost.ptr(), elem_step, rows_pyr[i], cols_pyr[i], nr_plane_pyr[i], rows_pyr[i+1], cols_pyr[i+1], nr_plane_pyr[i+1], stream); cur_idx = new_idx; } calc_all_iterations(temp_.ptr(), u[cur_idx].ptr(), d[cur_idx].ptr(), l[cur_idx].ptr(), r[cur_idx].ptr(), data_cost_selected.ptr(), disp_selected_pyr[cur_idx].ptr(), elem_step, rows_pyr[i], cols_pyr[i], nr_plane_pyr[i], iters_, max_disc_term_, disc_single_jump_, stream); } } else { for (int i = levels_ - 1; i >= 0; i--) { if (i == levels_ - 1) { init_data_cost(left.ptr(), right.ptr(), temp_.ptr(), left.step, left.rows, left.cols, disp_selected_pyr[cur_idx].ptr(), data_cost_selected.ptr(), elem_step, rows_pyr[i], cols_pyr[i], i, nr_plane_pyr[i], ndisp_, left.channels(), data_weight_, max_data_term_, min_disp_th_, use_local_init_data_cost_, stream); } else { compute_data_cost(left.ptr(), right.ptr(), left.step, disp_selected_pyr[cur_idx].ptr(), data_cost.ptr(), elem_step, left.rows, left.cols, rows_pyr[i], cols_pyr[i], rows_pyr[i+1], i, nr_plane_pyr[i+1], left.channels(), data_weight_, max_data_term_, min_disp_th_, stream); int new_idx = (cur_idx + 1) & 1; init_message(temp_.ptr(), u[new_idx].ptr(), d[new_idx].ptr(), l[new_idx].ptr(), r[new_idx].ptr(), u[cur_idx].ptr(), d[cur_idx].ptr(), l[cur_idx].ptr(), r[cur_idx].ptr(), disp_selected_pyr[new_idx].ptr(), disp_selected_pyr[cur_idx].ptr(), data_cost_selected.ptr(), data_cost.ptr(), elem_step, rows_pyr[i], cols_pyr[i], nr_plane_pyr[i], rows_pyr[i+1], cols_pyr[i+1], nr_plane_pyr[i+1], stream); cur_idx = new_idx; } calc_all_iterations(temp_.ptr(), u[cur_idx].ptr(), d[cur_idx].ptr(), l[cur_idx].ptr(), r[cur_idx].ptr(), data_cost_selected.ptr(), disp_selected_pyr[cur_idx].ptr(), elem_step, rows_pyr[i], cols_pyr[i], nr_plane_pyr[i], iters_, max_disc_term_, disc_single_jump_, stream); } } const int dtype = disp.fixedType() ? disp.type() : CV_16SC1; disp.create(rows, cols, dtype); GpuMat out = disp.getGpuMat(); if (dtype != CV_16SC1) { outBuf_.create(rows, cols, CV_16SC1); out = outBuf_; } out.setTo(0, _stream); if (msg_type_ == CV_32F) { compute_disp(u[cur_idx].ptr(), d[cur_idx].ptr(), l[cur_idx].ptr(), r[cur_idx].ptr(), data_cost_selected.ptr(), disp_selected_pyr[cur_idx].ptr(), elem_step, out, nr_plane_pyr[0], stream); } else { compute_disp(u[cur_idx].ptr(), d[cur_idx].ptr(), l[cur_idx].ptr(), r[cur_idx].ptr(), data_cost_selected.ptr(), disp_selected_pyr[cur_idx].ptr(), elem_step, out, nr_plane_pyr[0], stream); } if (dtype != CV_16SC1) out.convertTo(disp, dtype, _stream); } void StereoCSBPImpl::compute(InputArray /*data*/, OutputArray /*disparity*/, Stream& /*stream*/) { CV_Error(Error::StsNotImplemented, "Not implemented"); } } Ptr cv::cuda::createStereoConstantSpaceBP(int ndisp, int iters, int levels, int nr_plane, int msg_type) { return makePtr(ndisp, iters, levels, nr_plane, msg_type); } void cv::cuda::StereoConstantSpaceBP::estimateRecommendedParams(int width, int height, int& ndisp, int& iters, int& levels, int& nr_plane) { ndisp = (int) ((float) width / 3.14f); if ((ndisp & 1) != 0) ndisp++; int mm = std::max(width, height); iters = mm / 100 + ((mm > 1200)? - 4 : 4); levels = (int)::log(static_cast(mm)) * 2 / 3; if (levels == 0) levels++; nr_plane = (int) ((float) ndisp / std::pow(2.0, levels + 1)); } #endif /* !defined (HAVE_CUDA) */